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ORCIDSuhas Lohit
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2020 – today
- 2024
[c28]Haomiao Ni, Bernhard Egger, Suhas Lohit, Anoop Cherian, Ye Wang, Toshiaki Koike-Akino, Sharon X. Huang, Tim K. Marks:
TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. CVPR 2024: 9015-9025- [c27]Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang, Pedro Miraldo, Suhas Lohit, Moitreya Chatterjee:
Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-Aware Spatio-Temporal Sampling. CVPR 2024: 19667-19679 - [c26]Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel:
Equivariant Spatio-temporal Self-supervision for LiDAR Object Detection. ECCV (26) 2024: 475-491 - [c25]Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael J. Jones, Walter J. Scheirer:
Pixel-Grounded Prototypical Part Networks. WACV 2024: 4756-4767 - [i24]Sourya Basu, Suhas Lohit, Matthew Brand:
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups. CoRR abs/2402.15413 (2024) - [i23]Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel:
Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection. CoRR abs/2404.11737 (2024) - [i22]Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel:
Multimodal 3D Object Detection on Unseen Domains. CoRR abs/2404.11764 (2024) - [i21]Haomiao Ni, Bernhard Egger, Suhas Lohit, Anoop Cherian, Ye Wang, Toshiaki Koike-Akino, Sharon X. Huang, Tim K. Marks:
TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. CoRR abs/2404.16306 (2024) - [i20]Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang, Pedro Miraldo, Suhas Lohit, Moitreya Chatterjee:
Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling. CoRR abs/2406.03723 (2024) - [i19]Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Joanna Matthiesen, Kevin Smith, Joshua B. Tenenbaum:
Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads. CoRR abs/2406.15736 (2024) - 2023
- [c24]Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin A. Smith, Joshua B. Tenenbaum:
Are Deep Neural Networks SMARTer Than Second Graders? CVPR 2023: 10834-10844 - [c23]Eun Som Jeon, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga:
Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks. ICASSP 2023: 1-5 - [c22]Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M. Patel, Tim K. Marks:
Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. ICCV 2023: 20793-20803 - [c21]Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael N. Jones:
Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. ICCV (Workshops) 2023: 924-932 - [c20]Vineet R. Shenoy, Tim K. Marks, Hassan Mansour, Suhas Lohit:
Unrolled iPPG: Video Heart Rate Estimation via Unrolling Proximal Gradient Descent. ICIP 2023: 2715-2719 - [i18]Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael N. Jones, Walter J. Scheirer:
Pixel-Grounded Prototypical Part Networks. CoRR abs/2309.14531 (2023) - [i17]Manish Sharma
, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael Jones:
Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. CoRR abs/2309.16592 (2023) - [i16]Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M. Patel, Tim K. Marks:
Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. CoRR abs/2310.00224 (2023) - 2022
- [c19]Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael Jones, Amit K. Roy-Chowdhury:
Cross-Modal Knowledge Transfer Without Task-Relevant Source Data. ECCV (34) 2022: 111-127 - [c18]Hassan Mansour, Suhas Lohit, Petros T. Boufounos:
Distributed Radar Autofocus Imaging Using Deep Priors. ICIP 2022: 2511-2515 - [c17]David W. Romero, Suhas Lohit:
Learning Partial Equivariances From Data. NeurIPS 2022 - [c16]Huan Wang, Suhas Lohit, Michael N. Jones, Yun Fu:
What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective. NeurIPS 2022 - [c15]Suhas Lohit, Michael Jones:
Model Compression Using Optimal Transport. WACV 2022: 3645-3654 - [i15]Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Amit K. Roy-Chowdhury:
Cross-Modal Knowledge Transfer Without Task-Relevant Source Data. CoRR abs/2209.04027 (2022) - [i14]Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin A. Smith, Joshua B. Tenenbaum:
Are Deep Neural Networks SMARTer than Second Graders? CoRR abs/2212.09993 (2022) - 2021
- [c14]Armand Comas, Tim K. Marks, Hassan Mansour, Suhas Lohit, Yechi Ma, Xiaoming Liu:
Turnip: Time-Series U-Net With Recurrence For NIR Imaging PPG. ICIP 2021: 309-313 - [c13]Suhas Lohit, Rushil Anirudh, Pavan K. Turaga:
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. WACV 2021: 2341-2350 - [c12]Rushil Anirudh, Suhas Lohit, Pavan K. Turaga:
Generative Patch Priors for Practical Compressive Image Recovery. WACV 2021: 2534-2544 - [i13]David W. Romero, Suhas Lohit:
Learning Equivariances and Partial Equivariances from Data. CoRR abs/2110.10211 (2021) - 2020
- [c11]Kaushik Koneripalli, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga:
Rate-Invariant Autoencoding of Time-Series. ICASSP 2020: 3732-3736 - [i12]Rushil Anirudh, Suhas Lohit, Pavan K. Turaga:
Generative Patch Priors for Practical Compressive Image Recovery. CoRR abs/2006.10873 (2020) - [i11]Suhas Lohit, Rushil Anirudh, Pavan K. Turaga:
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. CoRR abs/2012.02043 (2020) - [i10]Huan Wang, Suhas Lohit, Michael Jones, Yun Fu:
Knowledge Distillation Thrives on Data Augmentation. CoRR abs/2012.02909 (2020) - [i9]Huan Wang, Suhas Lohit, Michael Jones, Yun Fu:
Multi-head Knowledge Distillation for Model Compression. CoRR abs/2012.02911 (2020) - [i8]Suhas Lohit, Michael Jones:
Model Compression Using Optimal Transport. CoRR abs/2012.03907 (2020) - [i7]Suhas Lohit, Shubhendu Trivedi:
Rotation-Invariant Autoencoders for Signals on Spheres. CoRR abs/2012.04474 (2020)
2010 – 2019
- 2019
- [c10]Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga:
Rank-Regularized Measurement Operators for Compressive Imaging. ACSSC 2019: 942-946 - [c9]Suhas Lohit, Qiao Wang, Pavan K. Turaga:
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping. CVPR 2019: 12426-12435 - [c8]Suhas Lohit, Dehong Liu, Hassan Mansour, Petros T. Boufounos:
Unrolled Projected Gradient Descent for Multi-spectral Image Fusion. ICASSP 2019: 7725-7729 - [i6]Suhas Lohit, Qiao Wang, Pavan K. Turaga:
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping. CoRR abs/1906.05947 (2019) - 2018
- [j1]Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok:
Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images. IEEE Trans. Computational Imaging 4(3): 326-340 (2018) - [c7]Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker K. Pillai, Pavan K. Turaga, Rama Chellappa:
Predicting Dynamical Evolution of Human Activities From a Single Image. CVPR Workshops 2018: 383-392 - [c6]Li-Chi Huang, Kuldeep Kulkarni, Anik Jha, Suhas Lohit, Suren Jayasuriya, Pavan K. Turaga:
CS-VQA: Visual Question Answering with Compressively Sensed Images. ICIP 2018: 1283-1287 - [i5]Li-Chi Huang, Kuldeep Kulkarni, Anik Jha, Suhas Lohit, Suren Jayasuriya, Pavan K. Turaga:
CS-VQA: Visual Question Answering with Compressively Sensed Images. CoRR abs/1806.03379 (2018) - [i4]Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga:
Rate-Adaptive Neural Networks for Spatial Multiplexers. CoRR abs/1809.02850 (2018) - 2017
- [c5]Suhas Lohit, Pavan K. Turaga:
Learning Invariant Riemannian Geometric Representations Using Deep Nets. ICCV Workshops 2017: 1329-1338 - [i3]Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok:
Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images. CoRR abs/1708.04669 (2017) - [i2]Suhas Lohit, Pavan K. Turaga:
Learning Invariant Riemannian Geometric Representations Using Deep Nets. CoRR abs/1708.09485 (2017) - 2016
- [c4]Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok:
ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements. CVPR 2016: 449-458 - [c3]Qiao Wang, Suhas Lohit, Meynard John Toledo, Matthew P. Buman, Pavan K. Turaga:
A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer. EMBC 2016: 2631-2635 - [c2]Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga:
Direct inference on compressive measurements using convolutional neural networks. ICIP 2016: 1913-1917 - [i1]Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok:
ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Random Measurements. CoRR abs/1601.06892 (2016) - 2015
- [c1]Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga, Jian Wang, Aswin C. Sankaranarayanan:
Reconstruction-free inference on compressive measurements. CVPR Workshops 2015: 16-24
Coauthor Index
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last updated on 2024-11-15 20:38 CET by the dblp team
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