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ORCIDVineeth N. Balasubramanian
Vineeth Nallure Balasubramanian – Vineeth Balasubramanian
Person information
- affiliation: Indian Institute of Technology, Hyderabad, Department of Computer Science and Engineering
- affiliation: Arizona State University, Tempe, Department of Computer Science and Engineering
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2020 – today
- 2024
[j13]Thrupthi Ann John
, Vineeth N. Balasubramanian, C. V. Jawahar:
Explaining Deep Face Algorithms Through Visualization: A Survey. IEEE Trans. Biom. Behav. Identity Sci. 6(1): 15-29 (2024)- [c127]Sandesh Kamath, Sankalp Mittal, Amit Deshpande, Vineeth N. Balasubramanian:
Rethinking Robustness of Model Attributions. AAAI 2024: 2688-2696 - [c126]Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian:
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation. AAAI 2024: 14793-14801 - [c125]Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin Godfrey L, Varshaneya V, Vineeth N. Balasubramanian, Satyanarayan Kar:
Towards Learning and Explaining Indirect Causal Effects in Neural Networks. AAAI 2024: 14802-14810 - [c124]Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Gaurav Sinha:
Interpretable Model Drift Detection. COMAD/CODS 2024: 1-9 - [c123]Tarun Ram Menta, Surgan Jandial, Akash Patil, Saketh Bachu, Vimal K. B., Balaji Krishnamurthy, Vineeth N. Balasubramanian, Mausoom Sarkar, Chirag Agarwal:
Active Transferability Estimation. CVPR Workshops 2024: 2659-2670 - [c122]Prachi Garg, K. J. Joseph, Vineeth N. Balasubramanian, Necati Cihan Camgöz, Chengde Wan, Kenrick Kin, Weiguang Si, Shugao Ma, Fernando De la Torre:
POET: Prompt Offset Tuning for Continual Human Action Adaptation. ECCV (64) 2024: 436-455 - [c121]Pranoy Panda, Siddharth Tandon, Vineeth N. Balasubramanian:
FW-Shapley: Real-Time Estimation of Weighted Shapley Values. ICASSP 2024: 6210-6214 - [c120]Sairam VC Rebbapragada, Pranoy Panda, Vineeth N. Balasubramanian:
C2FDrone: Coarse-to-Fine Drone-to-Drone Detection using Vision Transformer Networks. ICRA 2024: 6627-6633 - [c119]Hiran Sarkar, Vishal M. Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth N. Balasubramanian:
Open-Set Object Detection By Aligning Known Class Representations. WACV 2024: 218-227 - [c118]Bhat Dittakavi, Bharathi Callepalli, Aleti Vardhan, Sai Vikas Desai, Vineeth N. Balasubramanian:
CARE: Counterfactual-based Algorithmic Recourse for Explainable Pose Correction. WACV 2024: 4890-4899 - [i91]Tanmay Garg, Deepika Vemuri, Vineeth N. Balasubramanian:
Advancing Ante-Hoc Explainable Models through Generative Adversarial Networks. CoRR abs/2401.04647 (2024) - [i90]Purbayan Kar, Vishal M. Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth Balasubramanian:
Fiducial Focus Augmentation for Facial Landmark Detection. CoRR abs/2402.15044 (2024) - [i89]Sairam VC Rebbapragada, Pranoy Panda, Vineeth N. Balasubramanian:
C2FDrone: Coarse-to-Fine Drone-to-Drone Detection using Vision Transformer Networks. CoRR abs/2404.19276 (2024) - [i88]Hari Chandana Kuchibhotla, Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian:
Can Better Text Semantics in Prompt Tuning Improve VLM Generalization? CoRR abs/2405.07921 (2024) - [i87]Aniket Vashishtha, Abhinav Kumar, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma:
Teaching Transformers Causal Reasoning through Axiomatic Training. CoRR abs/2407.07612 (2024) - [i86]Vishal M. Chudasama, Hiran Sarkar, Pankaj Wasnik, Vineeth N. Balasubramanian, Jayateja Kalla:
Beyond Few-shot Object Detection: A Detailed Survey. CoRR abs/2408.14249 (2024) - [i85]Rahul Ramachandran, Tejal Kulkarni, Charchit Sharma, Deepak Vijaykeerthy, Vineeth N. Balasubramanian:
On Evaluation of Vision Datasets and Models using Human Competency Frameworks. CoRR abs/2409.04041 (2024) - 2023
- [c117]Purbayan Kar, Vishal M. Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth Balasubramanian:
Fiducial Focus Augmentation for Facial Landmark Detection. BMVC 2023: 562-565 - [c116]Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian:
Weakly-supervised Spatially Grounded Concept Learner for Few-Shot Learning. BMVC 2023: 858-867 - [c115]Surgan Jandial, Yash Khasbage, Arghya Pal, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
RetroKD : Leveraging Past States for Regularizing Targets in Teacher-Student Learning. COMAD/CODS 2023: 10-18 - [c114]Vimal K. B., Saketh Bachu, Tanmay Garg, Niveditha Lakshmi Narasimhan, Raghavan Konuru, Vineeth N. Balasubramanian:
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach. ICCV 2023: 11575-11586 - [c113]Shubhra Aich, Jesús Ruiz-Santaquiteria, Zhenyu Lu, Prachi Garg, K. J. Joseph, Alvaro Fernandez Garcia, Vineeth N. Balasubramanian, Kenrick Kin, Chengde Wan, Necati Cihan Camgöz, Shugao Ma, Fernando De la Torre:
Data-Free Class-Incremental Hand Gesture Recognition. ICCV 2023: 20901-20910 - [c112]Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian:
Mitigating the Effect of Incidental Correlations on Part-based Learning. NeurIPS 2023 - [c111]Aveen Dayal, Vimal K. B., Linga Reddy Cenkeramaddi, C. Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian:
MADG: Margin-based Adversarial Learning for Domain Generalization. NeurIPS 2023 - [c110]Rebbapragada V. C. Sairam, Monish Keswani, Uttaran Sinha, Nishit Shah, Vineeth N. Balasubramanian:
ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection. WACV 2023: 3708-3717 - [c109]Gaurav Bhatt, Vineeth N. Balasubramanian:
Learning Style Subspaces for Controllable Unpaired Domain Translation. WACV 2023: 4209-4218 - [i84]Tarun Ram Menta, Surgan Jandial, Akash Patil, Vimal KB, Saketh Bachu, Balaji Krishnamurthy, Vineeth N. Balasubramanian, Chirag Agarwal, Mausoom Sarkar:
Towards Estimating Transferability using Hard Subsets. CoRR abs/2301.06928 (2023) - [i83]Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin L. Godfrey, Vineeth N. Balasubramanian, Varshaneya V, Satya Narayanan Kar:
Learning Causal Attributions in Neural Networks: Beyond Direct Effects. CoRR abs/2303.13850 (2023) - [i82]Chaitanya Devaguptapu, Samarth Sinha, K. J. Joseph, Vineeth N. Balasubramanian, Animesh Garg:
Δ-Networks for Efficient Model Patching. CoRR abs/2303.14772 (2023) - [i81]Abbavaram Gowtham Reddy, Saketh Bachu, Saloni Dash, Charchit Sharma, Amit Sharma, Vineeth N. Balasubramanian:
Rethinking Counterfactual Data Augmentation Under Confounding. CoRR abs/2305.18183 (2023) - [i80]Vimal KB, Saketh Bachu, Tanmay Garg, Niveditha Lakshmi Narasimhan, Raghavan Konuru, Vineeth N. Balasubramanian:
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach. CoRR abs/2309.02429 (2023) - [i79]Thrupthi Ann John, Vineeth N. Balasubramanian, C. V. Jawahar:
Explaining Deep Face Algorithms through Visualization: A Survey. CoRR abs/2309.14715 (2023) - [i78]Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian:
Mitigating the Effect of Incidental Correlations on Part-based Learning. CoRR abs/2310.00377 (2023) - [i77]Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma:
Causal Inference Using LLM-Guided Discovery. CoRR abs/2310.15117 (2023) - [i76]Aveen Dayal, Vimal K. B., Linga Reddy Cenkeramaddi, C. Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian:
MADG: Margin-based Adversarial Learning for Domain Generalization. CoRR abs/2311.08503 (2023) - [i75]Sandesh Kamath, Sankalp Mittal, Amit Deshpande, Vineeth N. Balasubramanian:
Rethinking Robustness of Model Attributions. CoRR abs/2312.10534 (2023) - 2022
- [j12]Vineeth N. Balasubramanian:
Toward explainable deep learning. Commun. ACM 65(11): 68-69 (2022) - [j11]K. J. Joseph, Jathushan Rajasegaran, Salman H. Khan, Fahad Shahbaz Khan, Vineeth N. Balasubramanian:
Incremental Object Detection via Meta-Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9209-9216 (2022) - [c108]Abbavaram Gowtham Reddy, Benin Godfrey L, Vineeth N. Balasubramanian:
On Causally Disentangled Representations. AAAI 2022: 8089-8097 - [c107]Arjun Ashok, Chaitanya Devaguptapu, Vineeth N. Balasubramanian:
Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract). AAAI 2022: 12905-12906 - [c106]Piyushi Manupriya, Tarun Ram Menta, Saketha Nath Jagarlapudi, Vineeth N. Balasubramanian:
Improving Attribution Methods by Learning Submodular Functions. AISTATS 2022: 2173-2190 - [c105]Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam, Vineeth N. Balasubramanian:
Universalization of Any Adversarial Attack using Very Few Test Examples. COMAD/CODS 2022: 72-80 - [c104]Bhat Dittakavi, Divyagna Bavikadi, Sai Vikas Desai, Soumi Chakraborty, Nishant Reddy, Vineeth N. Balasubramanian, Bharathi Callepalli, Ayon Sharma:
Pose Tutor: An Explainable System for Pose Correction in the Wild. CVPR Workshops 2022: 3539-3548 - [c103]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Spacing Loss for Discovering Novel Categories. CVPR Workshops 2022: 3760-3765 - [c102]K. J. Joseph, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, Vineeth N. Balasubramanian:
Energy-based Latent Aligner for Incremental Learning. CVPR 2022: 7442-7451 - [c101]Hari Chandana Kuchibhotla, Sumitra S. Malagi, Shivam Chandhok, Vineeth N. Balasubramanian:
Unseen Classes at a Later Time? No Problem. CVPR 2022: 9235-9244 - [c100]Monish Keswani, Sriranjani Ramakrishnan, Nishant Reddy, Vineeth N. Balasubramanian:
Proto2Proto: Can you recognize the car, the way I do? CVPR 2022: 10223-10233 - [c99]Anirban Sarkar, Deepak Vijaykeerthy, Anindya Sarkar, Vineeth N. Balasubramanian:
A Framework for Learning Ante-hoc Explainable Models via Concepts. CVPR 2022: 10276-10285 - [c98]Arjun Ashok, K. J. Joseph, Vineeth N. Balasubramanian:
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer. ECCV (27) 2022: 105-122 - [c97]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Novel Class Discovery Without Forgetting. ECCV (24) 2022: 570-586 - [c96]Surgan Jandial, Yash Khasbage, Arghya Pal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Distilling the Undistillable: Learning from a Nasty Teacher. ECCV (13) 2022: 587-603 - [c95]Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma:
Matching Learned Causal Effects of Neural Networks with Domain Priors. ICML 2022: 10676-10696 - [c94]Deepak Kumar Singh, Shyam Nandan Rai, K. J. Joseph, Rohit Saluja, Vineeth N. Balasubramanian, Chetan Arora, Anbumani Subramanian, C. V. Jawahar:
New Objects on the Road? No Problem, We'll Learn Them Too. IROS 2022: 1972-1978 - [c93]Thrupthi Ann John, Isha Dua, Vineeth N. Balasubramanian, C. V. Jawahar:
ETL: Efficient Transfer Learning for Face Tasks. VISIGRAPP (5: VISAPP) 2022: 248-257 - [c92]Vaishnavi Khindkar, Chetan Arora, Vineeth N. Balasubramanian, Anbumani Subramanian, Rohit Saluja, C. V. Jawahar:
To miss-attend is to misalign! Residual Self-Attentive Feature Alignment for Adapting Object Detectors. WACV 2022: 376-386 - [c91]Shyam Nandan Rai, Rohit Saluja, Chetan Arora, Vineeth N. Balasubramanian, Anbumani Subramanian, C. V. Jawahar:
FLUID: Few-Shot Self-Supervised Image Deraining. WACV 2022: 418-427 - [c90]Puneet Mangla, Shivam Chandhok, Vineeth N. Balasubramanian, Fahad Shahbaz Khan:
COCOA: Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains. WACV 2022: 1618-1627 - [c89]Prachi Garg, Rohit Saluja, Vineeth N. Balasubramanian, Chetan Arora, Anbumani Subramanian, C. V. Jawahar:
Multi-Domain Incremental Learning for Semantic Segmentation. WACV 2022: 2080-2090 - [c88]Puneet Mangla, Nupur Kumari, Mayank Singh, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
Data InStance Prior (DISP) in Generative Adversarial Networks. WACV 2022: 3471-3481 - [c87]Anindya Sarkar, Anirban Sarkar, Vineeth N. Balasubramanian:
Leveraging Test-Time Consensus Prediction for Robustness against Unseen Noise. WACV 2022: 3564-3573 - [c86]Saloni Dash, Vineeth N. Balasubramanian, Amit Sharma:
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals. WACV 2022: 3879-3888 - [e2]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India. Proceedings of Machine Learning Research 189, PMLR 2022 [contents] - [i74]K. J. Joseph, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, Vineeth N. Balasubramanian:
Energy-based Latent Aligner for Incremental Learning. CoRR abs/2203.14952 (2022) - [i73]Hari Chandana Kuchibhotla, Sumitra S. Malagi, Shivam Chandhok, Vineeth N. Balasubramanian:
Unseen Classes at a Later Time? No Problem. CoRR abs/2203.16517 (2022) - [i72]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Spacing Loss for Discovering Novel Categories. CoRR abs/2204.10595 (2022) - [i71]Monish Keswani, Sriranjani Ramakrishnan, Nishant Reddy, Vineeth N. Balasubramanian:
Proto2Proto: Can you recognize the car, the way I do? CoRR abs/2204.11830 (2022) - [i70]Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models. CoRR abs/2205.03859 (2022) - [i69]Puneet Mangla, Shivam Chandhok, Milan Aggarwal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
INDIGO: Intrinsic Multimodality for Domain Generalization. CoRR abs/2206.05912 (2022) - [i68]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Novel Class Discovery without Forgetting. CoRR abs/2207.10659 (2022) - [i67]Arjun Ashok, Chaitanya Devaguptapu, Vineeth Balasubramanian:
Learning Modular Structures That Generalize Out-of-Distribution. CoRR abs/2208.03753 (2022) - [i66]Arjun Ashok, K. J. Joseph, Vineeth Balasubramanian:
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer. CoRR abs/2208.03767 (2022) - [i65]Rebbapragada V. C. Sairam, Monish Keswani, Uttaran Sinha, Nishit Shah, Vineeth N. Balasubramanian:
ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection. CoRR abs/2210.04574 (2022) - [i64]Surgan Jandial, Yash Khasbage, Arghya Pal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Distilling the Undistillable: Learning from a Nasty Teacher. CoRR abs/2210.11728 (2022) - [i63]Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian:
Counterfactual Generation Under Confounding. CoRR abs/2210.12368 (2022) - [i62]Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian:
Estimating Treatment Effects using Neurosymbolic Program Synthesis. CoRR abs/2211.04370 (2022) - [i61]Amlan Jyoti, Karthik Balaji Ganesh, Manoj Gayala, Nandita Lakshmi Tunuguntla, Sandesh Kamath, Vineeth N. Balasubramanian:
On the Robustness of Explanations of Deep Neural Network Models: A Survey. CoRR abs/2211.04780 (2022) - 2021
- [j10]Puneet Mangla, Vedant Singh, Shreyas Jayant Havaldar, Vineeth Balasubramanian:
On the benefits of defining vicinal distributions in latent space. Pattern Recognit. Lett. 152: 382-390 (2021) - [j9]Thrupthi Ann John, Vineeth N. Balasubramanian, C. V. Jawahar:
Canonical Saliency Maps: Decoding Deep Face Models. IEEE Trans. Biom. Behav. Identity Sci. 3(4): 561-572 (2021) - [c85]Anindya Sarkar, Anirban Sarkar, Vineeth N. Balasubramanian:
Enhanced Regularizers for Attributional Robustness. AAAI 2021: 2532-2540 - [c84]Adepu Ravi Sankar, Yash Khasbage, Rahul Vigneswaran, Vineeth N. Balasubramanian:
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization. AAAI 2021: 9481-9488 - [c83]Shivam Chandhok, Sanath Narayan, Hisham Cholakkal, Rao Muhammad Anwer, Vineeth N. Balasubramanian, Fahad Shahbaz Khan, Ling Shao:
Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains. BMVC 2021: 207 - [c82]Aditya Bharti, Vineeth Nallure Balasubramanian, C. V. Jawahar:
Towards Label-Free Few-Shot Learning: How Far Can We Go? CVIP (1) 2021: 256-268 - [c81]Radhika Dua, Sai Srinivas Kancheti, Vineeth N. Balasubramanian:
Beyond VQA: Generating Multi-Word Answers and Rationales to Visual Questions. CVPR Workshops 2021: 1623-1632 - [c80]Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian:
Instance-Wise Causal Feature Selection for Model Interpretation. CVPR Workshops 2021: 1756-1759 - [c79]K. J. Joseph, Salman H. Khan, Fahad Shahbaz Khan, Vineeth N. Balasubramanian:
Towards Open World Object Detection. CVPR 2021: 5830-5840 - [c78]Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, Pulkit Gopalani, Vineeth N. Balasubramanian:
On Adversarial Robustness: A Neural Architecture Search perspective. ICCVW 2021: 152-161 - [c77]Varshaneya V, S. Balasubramanian, Vineeth Balasubramanian:
Teaching GANs to sketch in vector format. ICVGIP 2021: 1:1-1:8 - [c76]Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi:
Feature generation for long-tail classification. ICVGIP 2021: 41:1-41:9 - [c75]Anindya Sarkar, Anirban Sarkar, Sowrya Gali, Vineeth N. Balasubramanian:
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach. NeurIPS 2021: 12836-12848 - [c74]Sandesh Kamath, Amit Deshpande, Subrahmanyam Kambhampati Venkata, Vineeth N. Balasubramanian:
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks. NeurIPS 2021: 27462-27474 - [c73]Vaasudev Narayanan, Aniket Anand Deshmukh, Ürün Dogan, Vineeth N. Balasubramanian:
On Challenges in Unsupervised Domain Generalization. Pre-Registration Workshop @ NeurIPS 2021: 42-58 - [c72]Shivam Chandhok, Vineeth N. Balasubramanian:
Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning. WACV 2021: 3099-3107 - [e1]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event. Proceedings of Machine Learning Research 157, PMLR 2021 [contents] - [i60]K. J. Joseph, Salman H. Khan, Fahad Shahbaz Khan, Vineeth N. Balasubramanian:
Towards Open World Object Detection. CoRR abs/2103.02603 (2021) - [i59]Piyushi Manupriya, Saketha Nath Jagarlapudi, Tarun Ram Menta, Vineeth N. Balasubramanian:
Improving Attribution Methods by Learning Submodular Functions. CoRR abs/2104.09073 (2021) - [i58]Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian:
Instance-wise Causal Feature Selection for Model Interpretation. CoRR abs/2104.12759 (2021) - [i57]Thrupthi Ann John, Vineeth N. Balasubramanian, C. V. Jawahar:
Canonical Saliency Maps: Decoding Deep Face Models. CoRR abs/2105.01386 (2021) - [i56]Gaurav Bhatt, Shivam Chandhok, Vineeth N. Balasubramanian:
Learn from Anywhere: Rethinking Generalized Zero-Shot Learning with Limited Supervision. CoRR abs/2107.04952 (2021) - [i55]Shivam Chandhok, Sanath Narayan, Hisham Cholakkal, Rao Muhammad Anwer, Vineeth N. Balasubramanian, Fahad Shahbaz Khan, Ling Shao:
Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains. CoRR abs/2107.05622 (2021) - [i54]Puneet Mangla, Shivam Chandhok, Vineeth N. Balasubramanian, Fahad Shahbaz Khan:
Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains. CoRR abs/2107.07497 (2021) - [i53]Anirban Sarkar, Deepak Vijaykeerthy, Anindya Sarkar, Vineeth N. Balasubramanian:
Inducing Semantic Grouping of Latent Concepts for Explanations: An Ante-Hoc Approach. CoRR abs/2108.11761 (2021) - [i52]Prachi Garg, Rohit Saluja, Vineeth N. Balasubramanian, Chetan Arora, Anbumani Subramanian, C. V. Jawahar:
Multi-Domain Incremental Learning for Semantic Segmentation. CoRR abs/2110.12205 (2021) - [i51]Anindya Sarkar, Anirban Sarkar, Sowrya Gali, Vineeth N. Balasubramanian:
Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach. CoRR abs/2111.00295 (2021) - [i50]Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi:
Feature Generation for Long-tail Classification. CoRR abs/2111.05956 (2021) - [i49]Abbavaram Gowtham Reddy, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Amit Sharma:
Causal Regularization Using Domain Priors. CoRR abs/2111.12490 (2021) - [i48]Abbavaram Gowtham Reddy, Benin Godfrey L, Vineeth N. Balasubramanian:
On Causally Disentangled Representations. CoRR abs/2112.05746 (2021) - 2020
- [j8]Kee-Eung Kim, Vineeth N. Balasubramanian:
Foreword: special issue for the journal track of the 12th Asian conference on machine learning (ACML 2020). Mach. Learn. 109(12): 2243-2245 (2020) - [j7]Vaibhav B. Sinha, Sneha Kudugunta, Adepu Ravi Sankar, Surya Teja Chavali, Vineeth N. Balasubramanian:
DANTE: Deep alternations for training neural networks. Neural Networks 131: 127-143 (2020) - [c71]Udit Maniyar, K. J. Joseph, Aniket Anand Deshmukh, Ürün Dogan, Vineeth N. Balasubramanian:
Zero-Shot Domain Generalization. BMVC 2020 - [c70]Shyam Nandan Rai, Vineeth N. Balasubramanian, Anbumani Subramanian, C. V. Jawahar:
Spatial Feedback Learning to Improve Semantic Segmentation in Hot Weather. BMVC 2020 - [c69]Saurabh Ravindranath, Rahul Baburaj, Vineeth N. Balasubramanian, NageswaraRao Namburu, Sujit Gujar, C. V. Jawahar:
Human-Machine Collaboration for Face Recognition. COMAD/CODS 2020: 10-18 - [c68]Sai Vikas Desai, Vineeth N. Balasubramanian:
Towards Fine-grained Sampling for Active Learning in Object Detection. CVPR Workshops 2020: 4010-4014 - [c67]Mayank Singh, Nupur Kumari, Puneet Mangla, Abhishek Sinha, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Attributional Robustness Training Using Input-Gradient Spatial Alignment. ECCV (27) 2020: 515-533 - [c66]Sakshi Varshney, P. K. Srijith, Vineeth N. Balasubramanian:
STM-GAN: Sequentially Trained Multiple Generators for Mitigating Mode Collapse. ICONIP (5) 2020: 676-684 - [c65]Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. KDD 2020: 1123-1131 - [c64]K. J. Joseph, Vineeth Nallure Balasubramanian:
Meta-Consolidation for Continual Learning. NeurIPS 2020 - [c63]Puneet Mangla, Vedant Singh, Vineeth N. Balasubramanian:
On Saliency Maps and Adversarial Robustness. ECML/PKDD (2) 2020: 272-288 - [c62]Akshay L. Chandra, Sai Vikas Desai, Chaitanya Devaguptapu, Vineeth N. Balasubramanian:
On Initial Pools for Deep Active Learning. Preregister@NeurIPS 2020: 14-32 - [c61]Dikshant Gupta, Aditya Anantharaman, Nehal Mamgain, Sowmya Kamath S., Vineeth N. Balasubramanian, C. V. Jawahar:
A Multi-Space Approach to Zero-Shot Object Detection. WACV 2020: 1198-1206 - [c60]Puneet Mangla, Mayank Singh, Abhishek Sinha, Nupur Kumari, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Charting the Right Manifold: Manifold Mixup for Few-shot Learning. WACV 2020: 2207-2216 - [c59]Harshitha Machiraju, Vineeth N. Balasubramanian:
A Little Fog for a Large Turn. WACV 2020: 2891-2900 - [c58]Shyam Nandan Rai, Vineeth N. Balasubramanian, Anbumani Subramanian, C. V. Jawahar:
Munich to Dubai: How far is it for Semantic Segmentationƒ. WACV 2020: 2988-2997 - [i47]Harshitha Machiraju, Vineeth N. Balasubramanian:
A Little Fog for a Large Turn. CoRR abs/2001.05873 (2020) - [i46]Puneet Mangla, Vedant Singh, Shreyas Jayant Havaldar, Vineeth N. Balasubramanian:
VarMixup: Exploiting the Latent Space for Robust Training and Inference. CoRR abs/2003.06566 (2020) - [i45]K. J. Joseph, Jathushan Rajasegaran, Salman H. Khan, Fahad Shahbaz Khan, Vineeth Balasubramanian, Ling Shao:
Incremental Object Detection via Meta-Learning. CoRR abs/2003.08798 (2020) - [i44]Arghya Pal, Vineeth N. Balasubramanian:
Generative Adversarial Data Programming. CoRR abs/2005.00364 (2020) - [i43]Puneet Mangla, Vedant Singh, Vineeth N. Balasubramanian:
On Saliency Maps and Adversarial Robustness. CoRR abs/2006.07828 (2020) - [i42]Akshay L. Chandra, Sai Vikas Desai, Wei Guo, Vineeth N. Balasubramanian:
Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey. CoRR abs/2006.11391 (2020) - [i41]Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. CoRR abs/2006.13593 (2020) - [i40]Shivam Chandhok, Vineeth N. Balasubramanian:
Enhancing Generalized Zero-Shot Learning via Adversarial Visual-Semantic Interaction. CoRR abs/2007.07757 (2020) - [i39]Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, Vineeth N. Balasubramanian:
An Empirical Study on the Robustness of NAS based Architectures. CoRR abs/2007.08428 (2020) - [i38]Sandeep Inuganti, Vineeth N. Balasubramanian:
Assisting Scene Graph Generation with Self-Supervision. CoRR abs/2008.03555 (2020) - [i37]Udit Maniyar, K. J. Joseph, Aniket Anand Deshmukh, Ürün Dogan, Vineeth N. Balasubramanian:
Zero Shot Domain Generalization. CoRR abs/2008.07443 (2020) - [i36]K. J. Joseph, Vineeth N. Balasubramanian:
Meta-Consolidation for Continual Learning. CoRR abs/2010.00352 (2020) - [i35]Radhika Dua, Sai Srinivas Kancheti, Vineeth N. Balasubramanian:
Beyond VQA: Generating Multi-word Answer and Rationale to Visual Questions. CoRR abs/2010.12852 (2020) - [i34]Akshay L. Chandra, Sai Vikas Desai, Chaitanya Devaguptapu, Vineeth N. Balasubramanian:
On Initial Pools for Deep Active Learning. CoRR abs/2011.14696 (2020) - [i33]Adepu Ravi Sankar, Yash Khasbage, Rahul Vigneswaran, Vineeth N. Balasubramanian:
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization. CoRR abs/2012.03801 (2020) - [i32]Puneet Mangla, Nupur Kumari, Mayank Singh, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Data Instance Prior for Transfer Learning in GANs. CoRR abs/2012.04256 (2020) - [i31]Aditya Bharti, Vineeth N. Balasubramanian, C. V. Jawahar:
Few Shot Learning With No Labels. CoRR abs/2012.13751 (2020) - [i30]Anindya Sarkar, Anirban Sarkar, Vineeth N. Balasubramanian:
Enhanced Regularizers for Attributional Robustness. CoRR abs/2012.14395 (2020)
2010 – 2019
- 2019
- [c57]Sai Vikas Desai, Akshay Chandra Lagandula, Wei Guo, Seishi Ninomiya, Vineeth N. Balasubramanian:
An Adaptive Supervision Framework for Active Learning in Object Detection. BMVC 2019: 230 - [c56]Chaitanya Devaguptapu, Ninad Akolekar, Manuj M. Sharma, Vineeth N. Balasubramanian:
Borrow From Anywhere: Pseudo Multi-Modal Object Detection in Thermal Imagery. CVPR Workshops 2019: 1029-1038 - [c55]Arghya Pal, Vineeth N. Balasubramanian:
Zero-Shot Task Transfer. CVPR 2019: 2189-2198 - [c54]Surgan Jandial, Puneet Mangla, Sakshi Varshney, Vineeth Balasubramanian:
AdvGAN++: Harnessing Latent Layers for Adversary Generation. ICCV Workshops 2019: 2045-2048 - [c53]Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar, Vineeth N. Balasubramanian:
Neural Network Attributions: A Causal Perspective. ICML 2019: 981-990 - [c52]K. J. Joseph, Vamshi Teja R, Krishnakant Singh, Vineeth N. Balasubramanian:
Submodular Batch Selection for Training Deep Neural Networks. IJCAI 2019: 2677-2683 - [c51]Nupur Kumari, Mayank Singh, Abhishek Sinha, Harshitha Machiraju, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models. IJCAI 2019: 2779-2785 - [c50]K. J. Joseph, Arghya Pal, Sailaja Rajanala, Vineeth N. Balasubramanian:
C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis. WACV 2019: 358-366 - [c49]Tejaswi Kasarla, Gattigorla Nagendar, Guruprasad M. Hegde, Vineeth Balasubramanian, C. V. Jawahar:
Region-based active learning for efficient labeling in semantic segmentation. WACV 2019: 1109-1117 - [i29]Thrupthi Ann John, Isha Dua, Vineeth N. Balasubramanian, C. V. Jawahar:
Low-Cost Transfer Learning of Face Tasks. CoRR abs/1901.02675 (2019) - [i28]Sneha Kudugunta, Vaibhav B. Sinha, Adepu Ravi Sankar, Surya Teja Chavali, Purushottam Kar, Vineeth N. Balasubramanian:
DANTE: Deep AlterNations for Training nEural networks. CoRR abs/1902.00491 (2019) - [i27]Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar, Vineeth N. Balasubramanian:
Neural Network Attributions: A Causal Perspective. CoRR abs/1902.02302 (2019) - [i26]Arghya Pal, Vineeth N. Balasubramanian:
Zero-Shot Task Transfer. CoRR abs/1903.01092 (2019) - [i25]Varshaneya V, S. Balasubramanian, Vineeth N. Balasubramanian:
Teaching GANs to Sketch in Vector Format. CoRR abs/1904.03620 (2019) - [i24]Abhishek Sinha, Mayank Singh, Nupur Kumari, Balaji Krishnamurthy, Harshitha Machiraju, Vineeth N. Balasubramanian:
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models. CoRR abs/1905.05186 (2019) - [i23]Chaitanya Devaguptapu, Ninad Akolekar, Manuj M. Sharma, Vineeth N. Balasubramanian:
Borrow from Anywhere: Pseudo Multi-modal Object Detection in Thermal Imagery. CoRR abs/1905.08789 (2019) - [i22]Sai Vikas Desai, Vineeth N. Balasubramanian, Tokihiro Fukatsu, Seishi Ninomiya, Wei Guo:
Automatic estimation of heading date of paddy rice using deep learning. CoRR abs/1906.07917 (2019) - [i21]K. J. Joseph, Vamshi Teja R, Krishnakant Singh, Vineeth N. Balasubramanian:
Submodular Batch Selection for Training Deep Neural Networks. CoRR abs/1906.08771 (2019) - [i20]Puneet Mangla, Mayank Singh, Abhishek Sinha, Nupur Kumari, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Charting the Right Manifold: Manifold Mixup for Few-shot Learning. CoRR abs/1907.12087 (2019) - [i19]Puneet Mangla, Surgan Jandial, Sakshi Varshney, Vineeth N. Balasubramanian:
AdvGAN++ : Harnessing latent layers for adversary generation. CoRR abs/1908.00706 (2019) - [i18]Sai Vikas Desai, Akshay L. Chandra, Wei Guo, Seishi Ninomiya, Vineeth N. Balasubramanian:
An Adaptive Supervision Framework for Active Learning in Object Detection. CoRR abs/1908.02454 (2019) - [i17]Akshay L. Chandra, Sai Vikas Desai, Vineeth N. Balasubramanian, Seishi Ninomiya, Wei Guo:
Active Learning with Weak Supervision for Cost-Effective Panicle Detection in Cereal Crops. CoRR abs/1910.01789 (2019) - [i16]Mayank Singh, Nupur Kumari, Puneet Mangla, Abhishek Sinha, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
On the Benefits of Attributional Robustness. CoRR abs/1911.13073 (2019) - 2018
- [j6]Nakul Agarwal, Vineeth N. Balasubramanian, C. V. Jawahar:
Improving multiclass classification by deep networks using DAGSVM and Triplet Loss. Pattern Recognit. Lett. 112: 184-190 (2018) - [c48]Gattigorla Nagendar, Digvijay Singh, Vineeth N. Balasubramanian, C. V. Jawahar:
Neuro-IoU: Learning a Surrogate Loss for Semantic Segmentation. BMVC 2018: 278 - [c47]Adepu Ravi Sankar, Vineeth N. Balasubramanian:
Are saddles good enough for neural networks. COMAD/CODS 2018: 37-45 - [c46]Supriya Pandhre, Himangi Mittal, Manish Gupta, Vineeth N. Balasubramanian:
STwalk: learning trajectory representations in temporal graphs. COMAD/CODS 2018: 210-219 - [c45]Vishwak Srinivasan, Adepu Ravi Sankar, Vineeth N. Balasubramanian:
ADINE: an adaptive momentum method for stochastic gradient descent. COMAD/CODS 2018: 249-256 - [c44]Arghya Pal, Vineeth N. Balasubramanian:
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data. CVPR 2018: 1556-1565 - [c43]Pengfei Zhu, Longyin Wen, Dawei Du, Xiao Bian, Haibin Ling, Qinghua Hu, Qinqin Nie, Hao Cheng, Chenfeng Liu, Xiaoyu Liu, Wenya Ma, Haotian Wu, Lianjie Wang, Arne Schumann, Chase Brown, Qian Chen, Chengzheng Li, Dongdong Li, Emmanouil Michail, Fan Zhang, Feng Ni, Feng Zhu, Guanghui Wang, Haipeng Zhang, Han Deng, Hao Liu, Haoran Wang, Heqian Qiu, Honggang Qi, Honghui Shi, Hongliang Li, Hongyu Xu, Hu Lin, Ioannis Kompatsiaris, Jian Cheng, Jianqiang Wang, Jianxiu Yang, Jingkai Zhou, Juanping Zhao, K. J. Joseph, Kaiwen Duan, Karthik Suresh, Bo Ke, Ke Wang, Konstantinos Avgerinakis, Lars Wilko Sommer, Lei Zhang, Li Yang, Lin Cheng, Lin Ma, Liyu Lu, Lu Ding, Minyu Huang, Naveen Kumar Vedurupaka, Nehal Mamgain, Nitin Bansal, Oliver Acatay, Panagiotis Giannakeris, Qian Wang, Qijie Zhao, Qingming Huang, Qiong Liu, Qishang Cheng, Qiuchen Sun, Robert Laganière, Sheng Jiang, Shengjin Wang, Shubo Wei, Siwei Wang, Stefanos Vrochidis, Sujuan Wang, Tiaojio Lee, Usman Sajid, Vineeth N. Balasubramanian, Wei Li, Wei Zhang, Weikun Wu, Wenchi Ma, Wenrui He, Wenzhe Yang, Xiaoyu Chen, Xin Sun, Xinbin Luo, Xintao Lian, Xiufang Li, Yangliu Kuai, Yali Li, Yi Luo, Yifan Zhang, Yiling Liu, Ying Li, Yong Wang, Yongtao Wang, Yuanwei Wu, Yue Fan, Yunchao Wei, Yuqin Zhang, Zexin Wang, Zhangyang Wang, Zhaoyue Xia, Zhen Cui, Zhenwei He, Zhipeng Deng, Zhiyao Guo, Zichen Song:
VisDrone-DET2018: The Vision Meets Drone Object Detection in Image Challenge Results. ECCV Workshops (5) 2018: 437-468 - [c42]Parikshit Sakurikar, Ishit Mehta, Vineeth N. Balasubramanian, P. J. Narayanan:
RefocusGAN: Scene Refocusing Using a Single Image. ECCV (4) 2018: 519-535 - [c41]K. J. Joseph, Rajiv Chunilal Patel, Amit Srivastava, Uma Gupta, Vineeth N. Balasubramanian:
MASON: A Model AgnoStic ObjectNess Framework. ECCV Workshops (5) 2018: 642-658 - [c40]Aditya Chattopadhyay, Anirban Sarkar, Prantik Howlader, Vineeth N. Balasubramanian:
Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. WACV 2018: 839-847 - [i15]Vaibhav B. Sinha, Sukrut Rao, Vineeth N. Balasubramanian:
Fast Dawid-Skene: A Fast Vote Aggregation Scheme for Sentiment Classification. CoRR abs/1803.02781 (2018) - [i14]Arghya Pal, Vineeth N. Balasubramanian:
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data. CoRR abs/1803.05137 (2018) - [i13]Adepu Ravi Sankar, Vishwak Srinivasan, Vineeth N. Balasubramanian:
On the Analysis of Trajectories of Gradient Descent in the Optimization of Deep Neural Networks. CoRR abs/1807.08140 (2018) - [i12]K. J. Joseph, Vineeth N. Balasubramanian:
MASON: A Model AgnoStic ObjectNess Framework. CoRR abs/1809.07499 (2018) - [i11]K. J. Joseph, Arghya Pal, Sailaja Rajanala, Vineeth N. Balasubramanian:
C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis. CoRR abs/1809.10238 (2018) - 2017
- [c39]Sirnam Swetha, Vineeth N. Balasubramanian, C. V. Jawahar:
Sequence-to-Sequence Learning for Human Pose Correction in Videos. ACPR 2017: 298-303 - [c38]Tanya Marwah, Gaurav Mittal, Vineeth N. Balasubramanian:
Attentive Semantic Video Generation Using Captions. ICCV 2017: 1435-1443 - [c37]Dhaivat Bhatt, Danish Sodhi, Arghya Pal, Vineeth N. Balasubramanian, K. Madhava Krishna:
Have i reached the intersection: A deep learning-based approach for intersection detection from monocular cameras. IROS 2017: 4495-4500 - [c36]Gaurav Mittal, Tanya Marwah, Vineeth N. Balasubramanian:
Sync-DRAW: Automatic Video Generation using Deep Recurrent Attentive Architectures. ACM Multimedia 2017: 1096-1104 - [i10]Adepu Ravi Sankar, Vineeth N. Balasubramanian:
Are Saddles Good Enough for Deep Learning? CoRR abs/1706.02052 (2017) - [i9]Hemanth Venkateswara, Vineeth N. Balasubramanian, Prasanth Lade, Sethuraman Panchanathan:
Multiresolution Match Kernels for Gesture Video Classification. CoRR abs/1706.07530 (2017) - [i8]Tanya Marwah, Gaurav Mittal, Vineeth N. Balasubramanian:
Attentive Semantic Video Generation using Captions. CoRR abs/1708.05980 (2017) - [i7]Aditya Chattopadhyay, Anirban Sarkar, Prantik Howlader, Vineeth N. Balasubramanian:
Grad-CAM++: Generalized Gradient-based Visual Explanations for Deep Convolutional Networks. CoRR abs/1710.11063 (2017) - [i6]Supriya Pandhre, Himangi Mittal, Manish Gupta, Vineeth N. Balasubramanian:
STWalk: Learning Trajectory Representations in Temporal Graphs. CoRR abs/1711.04150 (2017) - [i5]Vishwak Srinivasan, Adepu Ravi Sankar, Vineeth N. Balasubramanian:
ADINE: An Adaptive Momentum Method for Stochastic Gradient Descent. CoRR abs/1712.07424 (2017) - 2016
- [c35]Aditya Kamath, Aradhya Biswas, Vineeth Balasubramanian:
A crowdsourced approach to student engagement recognition in e-learning environments. WACV 2016: 1-9 - [c34]Digvijay Singh, Vineeth Balasubramanian, C. V. Jawahar:
Fine-tuning human pose estimations in videos. WACV 2016: 1-9 - [i4]Abhay Gupta, Richik Jaiswal, Sagar Adhikari, Vineeth Balasubramanian:
DAISEE: Dataset for Affective States in E-Learning Environments. CoRR abs/1609.01885 (2016) - [i3]Bharat Bhusan Sau, Vineeth N. Balasubramanian:
Deep Model Compression: Distilling Knowledge from Noisy Teachers. CoRR abs/1610.09650 (2016) - [i2]Gaurav Mittal, Tanya Marwah, Vineeth N. Balasubramanian:
Sync-DRAW: Automatic GIF Generation using Deep Recurrent Attentive Architectures. CoRR abs/1611.10314 (2016) - [i1]Supriya Pandhre, Manish Gupta, Vineeth N. Balasubramanian:
Community-based Outlier Detection for Edge-attributed Graphs. CoRR abs/1612.09435 (2016) - 2015
- [j5]Vineeth Nallure Balasubramanian, Shayok Chakraborty, Sethuraman Panchanathan:
Conformal predictions for information fusion - A comparative study of p-value combination methods. Ann. Math. Artif. Intell. 74(1-2): 45-65 (2015) - [j4]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Qian Sun, Sethuraman Panchanathan, Jieping Ye:
Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds. IEEE Trans. Pattern Anal. Mach. Intell. 37(10): 1945-1958 (2015) - [j3]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Adaptive Batch Mode Active Learning. IEEE Trans. Neural Networks Learn. Syst. 26(8): 1747-1760 (2015) - [c33]Adepu Ravi Sankar, Vineeth N. Balasubramanian:
Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models. ACML 2015: 391-406 - [c32]M. Sai Rajeswar, Adepu Ravi Sankar, Vineeth N. Balasubramanian, C. D. Sudheer:
Scaling Up the Training of Deep CNNs for Human Action Recognition. IPDPS Workshops 2015: 1172-1177 - [c31]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Adepu Ravi Sankar, Sethuraman Panchanathan, Jieping Ye:
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification. KDD 2015: 99-108 - [c30]Ritvik Jaiswal, Vineeth N. Balasubramanian:
Model Selection Using Efficiency of Conformal Predictors. SLDS 2015: 291-300 - 2013
- [j2]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Generalized batch mode active learning for face-based biometric recognition. Pattern Recognit. 46(2): 497-508 (2013) - [c29]Shayok Chakraborty, Jiayu Zhou, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan, Ian Davidson, Jieping Ye:
Active Matrix Completion. ICDM 2013: 81-90 - [c28]Prasanth Lade, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Latent Facial Topics for affect analysis. ICME Workshops 2013: 1-6 - [c27]Prasanth Lade, Vineeth Nallure Balasubramanian, Hemanth Venkateswara, Sethuraman Panchanathan:
Detection of changes in human affect dimensions using an Adaptive Temporal Topic model. ICME 2013: 1-6 - [c26]Hemanth Venkateswara, Vineeth Nallure Balasubramanian, Prasanth Lade, Sethuraman Panchanathan:
Multiresolution Match Kernels for gesture video classification. ICME Workshops 2013: 1-4 - [c25]Vineeth Nallure Balasubramanian, Aaron Baker, Matthew Yanez, Shayok Chakraborty, Sethuraman Panchanathan:
PyCP: An Open-Source Conformal Predictions Toolkit. AIAI 2013: 361-370 - 2012
- [c24]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Batch Mode Active Learning for Multimedia Pattern Recognition. ISM 2012: 489-490 - [c23]Mohammad A. Alzubaidi, Vineeth Nallure Balasubramanian, Ameet Patel, Sethuraman Panchanathan, John A. Black Jr.:
Efficient atypicality detection in chest radiographs. ISSPA 2012: 193-198 - [c22]Mohammad A. Alzubaidi, Vineeth N. Balasubramanian, Ameet Patel, Sethuraman Panchanathan, John A. Black Jr.:
A novel semi-transductive learning framework for efficient atypicality detection in chest radiographs. Medical Imaging: Computer-Aided Diagnosis 2012: 83153A - [c21]Mohammad A. Alzubaidi, Vineeth N. Balasubramanian, Ameet Patel, Sethuraman Panchanathan, John A. Black Jr.:
A novel online Variance Based Instance Selection (VBIS) method for efficient atypicality detection in chest radiographs. Medical Imaging: Image Processing 2012: 83144Z - 2011
- [c20]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Dynamic Batch Mode Active Learning via L1 Regularization. AAAI 2011: 1764-1765 - [c19]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Dynamic batch mode active learning. CVPR 2011: 2649-2656 - [c18]Shayok Chakraborty, Hemanth Venkateswara, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Active Batch Selection for Fuzzy Classification in Facial Expression Recognition. ICMLA (1) 2011: 241-246 - [c17]Rita Chattopadhyay, Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Optimization-Based Domain Adaptation towards Person-Adaptive Classification Models. ICMLA (1) 2011: 476-483 - [c16]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Optimal batch selection for active learning in multi-label classification. ACM Multimedia 2011: 1413-1416 - 2010
- [b1]Vineeth Nallure Balasubramanian:
Conformal Predictions in Multimedia Pattern Recognition. Arizona State University, Tempe, USA, 2010 - [c15]Shayok Chakraborty, Vineeth N. Balasubramanian, Sethuraman Panchanathan:
Learning from summaries of videos: Applying batch mode active learning to face-based biometrics. CVPR Workshops 2010: 130-137 - [c14]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Dynamic Batch Size Selection for Batch Mode Active Learning in Biometrics. ICMLA 2010: 15-22 - [c13]Vineeth Nallure Balasubramanian, Shayok Chakraborty, Sethuraman Panchanathan, Jieping Ye:
Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework. ICMLA 2010: 235-242 - [c12]Sébastien Marcel, Chris McCool, Pavel Matejka, Timo Ahonen, Jan Cernocký, Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan, Chi-Ho Chan, Josef Kittler, Norman Poh, Benoit G. B. Fauve, Ondrej Glembek, Oldrich Plchot, Zdenek Jancik, Anthony Larcher, Christophe Lévy, Driss Matrouf, Jean-François Bonastre, Ping-Han Lee, Jui-Yu Hung, Si-Wei Wu, Yi-Ping Hung, Lukás Machlica, John S. D. Mason, Sandra Mau, Conrad Sanderson, David Monzo, Antonio Albiol, Hieu V. Nguyen, Li Bai, Yan Wang, Matti Niskanen, Markus Turtinen, Juan Arturo Nolazco-Flores, L. Paola García-Perera, Roberto Aceves-Lopez, Mauricio Villegas, Roberto Paredes:
On the Results of the First Mobile Biometry (MOBIO) Face and Speaker Verification Evaluation. ICPR Contests 2010: 210-225 - [c11]Mohammad A. Alzubaidi, Vineeth N. Balasubramanian, Ameet Patel, Sethuraman Panchanathan, John A. Black Jr.:
What catches a radiologist's eye? A comprehensive comparison of feature types for saliency prediction. Medical Imaging: Computer-Aided Diagnosis 2010: 76240W - [c10]Sreekar Krishna, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Enriching social situational awareness in remote interactions: insights and inspirations from disability focused research. ACM Multimedia 2010: 1275-1284
2000 – 2009
- 2009
- [c9]Ramkiran Gouripeddi, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan, Jenni Harris, Ambika Bhaskaran, Robert M. Siegel:
Predicting risk of complications following a drug eluting stent procedure: A SVM approach for imbalanced data. CBMS 2009: 1-7 - [c8]Vineeth Balasubramanian, Shayok Chakraborty, Sethuraman Panchanathan:
Generalized Query by Transduction for online active learning. ICCV Workshops 2009: 1378-1385 - 2008
- [j1]Vineeth Nallure Balasubramanian, Sreekar Krishna, Sethuraman Panchanathan:
Person-Independent Head Pose Estimation Using Biased Manifold Embedding. EURASIP J. Adv. Signal Process. 2008 (2008) - [c7]Sreekar Krishna, Vineeth Nallure Balasubramanian, Narayanan Chatapuram Krishnan, Colin Juillard, Terri Hedgpeth, Sethuraman Panchanathan:
A wearable wireless RFID system for accessible shopping environments. BODYNETS 2008: 29 - [c6]Vineeth N. Balasubramanian, Sethuraman Panchanathan, Shayok Chakraborty:
Multiple cue integration in transductive confidence machines for head pose classification. CVPR Workshops 2008: 1-8 - [c5]Sethuraman Panchanathan, Narayanan Chatapuram Krishnan, Sreekar Krishna, Troy McDaniel, Vineeth Nallure Balasubramanian:
Enriched human-centered multimedia computing through inspirations from disabilities and deficit-centered computing solutions. HCC 2008: 35-42 - 2007
- [c4]Vineeth Nallure Balasubramanian, Jieping Ye, Sethuraman Panchanathan:
Biased Manifold Embedding: A Framework for Person-Independent Head Pose Estimation. CVPR 2007 - [c3]Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
Biased manifold embedding for person-independent head pose estimation. VISAPP (2) 2007: 76-84 - [c2]Vineeth Balasubramanian, Sethuraman Panchanathan:
Biased Manifold Embedding: Supervised Isomap for Person-Independent Head Pose Estimation. VISIGRAPP (Selected Papers) 2007: 177-188 - 2006
- [c1]Kanav Kahol, Narayanan Chatapuram Krishnan, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan, Marshall L. Smith, John Ferrara:
Measuring movement expertise in surgical tasks. ACM Multimedia 2006: 719-722
Coauthor Index
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of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-14 20:59 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
