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2020 – today
- 2024
[c32]Renan A. Rojas-Gomez, Teck-Yian Lim, Minh N. Do, Raymond A. Yeh:
Making Vision Transformers Truly Shift-Equivariant. CVPR 2024: 5568-5577- [c31]Joshua Ahn, Haochen Wang, Raymond A. Yeh, Greg Shakhnarovich:
Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields. CVPR 2024: 20396-20405 - [c30]Chiao-An Yang, Ziwei Liu, Raymond A. Yeh:
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-Time. ECCV (21) 2024: 223-241 - [c29]Amber Yijia Zheng, Raymond A. Yeh:
IMMA: Immunizing Text-to-Image Models Against Malicious Adaptation. ECCV (39) 2024: 458-475 - [i33]Md Ashiqur Rahman
, Robert Joseph George, Mogab Elleithy, Daniel V. Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar:
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. CoRR abs/2403.12553 (2024) - [i32]Joshua Ahn, Haochen Wang, Raymond A. Yeh, Greg Shakhnarovich:
Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields. CoRR abs/2404.02155 (2024) - [i31]Jae Joong Lee, Bosheng Li, Sara Beery, Jonathan Huang, Songlin Fei, Raymond A. Yeh, Bedrich Benes:
Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors. CoRR abs/2407.10330 (2024) - [i30]Amber Yijia Zheng, Chiao-An Yang, Raymond A. Yeh:
Learning to Obstruct Few-Shot Image Classification over Restricted Classes. CoRR abs/2409.19210 (2024) - [i29]Chiao-An Yang, Ziwei Liu, Raymond A. Yeh:
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-Time. CoRR abs/2410.01083 (2024) - 2023
- [c28]Adnan Firoze, Cameron Wingren, Raymond A. Yeh, Bedrich Benes, Daniel G. Aliaga:
Tree Instance Segmentation with Temporal Contour Graph. CVPR 2023: 2193-2202 - [c27]Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, Greg Shakhnarovich:
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation. CVPR 2023: 12619-12629 - [c26]Chiao-An Yang, Meng-Lin Wu, Raymond A. Yeh, Yu-Chiang Frank Wang:
Consistent and Multi-Scale Scene Graph Transformer for Semantic-Guided Image Outpainting. ICIP 2023: 176-180 - [c25]Yuan-Ting Hu, Alexander G. Schwing, Raymond A. Yeh:
Surface Snapping Optimization Layer for Single Image Object Shape Reconstruction. ICML 2023: 13599-13609 - [c24]Md Ashiqur Rahman, Raymond A. Yeh:
Truly Scale-Equivariant Deep Nets with Fourier Layers. NeurIPS 2023 - [i28]Renan A. Rojas-Gomez, Teck-Yian Lim, Minh N. Do, Raymond A. Yeh:
Making Vision Transformers Truly Shift-Equivariant. CoRR abs/2305.16316 (2023) - [i27]Md Ashiqur Rahman, Raymond A. Yeh:
Truly Scale-Equivariant Deep Nets with Fourier Layers. CoRR abs/2311.02922 (2023) - [i26]Yijia Zheng, Raymond A. Yeh:
IMMA: Immunizing text-to-image Models against Malicious Adaptation. CoRR abs/2311.18815 (2023) - [i25]Boheng Zhao, Rana Hanocka, Raymond A. Yeh:
AmbiGen: Generating Ambigrams from Pre-trained Diffusion Model. CoRR abs/2312.02967 (2023) - 2022
- [c23]Renan A. Rojas-Gomez, Raymond A. Yeh, Minh N. Do, Anh Nguyen:
Inverting Adversarially Robust Networks for Image Synthesis. ACCV (6) 2022: 389-407 - [c22]Raymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, Alexander G. Schwing:
Equivariance Discovery by Learned Parameter-Sharing. AISTATS 2022: 1527-1545 - [c21]William Gao, April Wang, Gal Metzer, Raymond A. Yeh, Rana Hanocka:
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation. BMVC 2022: 365 - [c20]Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren, Alexander G. Schwing:
Total Variation Optimization Layers for Computer Vision. CVPR 2022: 701-711 - [c19]Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing, Minh N. Do, Raymond A. Yeh:
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks. NeurIPS 2022 - [i24]Raymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, Alexander G. Schwing:
Equivariance Discovery by Learned Parameter-Sharing. CoRR abs/2204.03640 (2022) - [i23]Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren, Alexander G. Schwing:
Total Variation Optimization Layers for Computer Vision. CoRR abs/2204.03643 (2022) - [i22]Jiahao Li, Greg Shakhnarovich, Raymond A. Yeh:
Adapting CLIP For Phrase Localization Without Further Training. CoRR abs/2204.03647 (2022) - [i21]Xiaodan Du, Raymond A. Yeh, Nicholas I. Kolkin, Eli Shechtman, Greg Shakhnarovich:
Text-Free Learning of a Natural Language Interface for Pretrained Face Generators. CoRR abs/2209.03953 (2022) - [i20]William Gao, April Wang, Gal Metzer, Raymond A. Yeh, Rana Hanocka:
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation. CoRR abs/2210.05735 (2022) - [i19]Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing, Minh N. Do, Raymond A. Yeh:
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks. CoRR abs/2210.08001 (2022) - [i18]Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, Greg Shakhnarovich:
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation. CoRR abs/2212.00774 (2022) - [i17]Ofek Pearl, Itai Lang, Yuhua Hu, Raymond A. Yeh, Rana Hanocka:
GeoCode: Interpretable Shape Programs. CoRR abs/2212.11715 (2022) - 2021
- [b1]Raymond A. Yeh:
Extracting and learning structures from data. University of Illinois Urbana-Champaign, USA, 2021 - [c18]Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing:
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction From Video Data. CVPR 2021: 1418-1428 - [c17]Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing:
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction From Video Data. CVPR Workshops 2021: 3364-3374 - [c16]Junzhe Zhu, Raymond A. Yeh, Mark Hasegawa-Johnson:
Multi-Decoder Dprnn: Source Separation for Variable Number of Speakers. ICASSP 2021: 3420-3424 - [c15]Iou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing:
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning. ICML 2021: 6826-6836 - [c14]Iou-Jen Liu, Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing:
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning. IROS 2021: 5603-5610 - [i16]Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing:
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data. CoRR abs/2105.08612 (2021) - [i15]Renan A. Rojas-Gomez, Raymond A. Yeh, Minh N. Do, Anh Nguyen:
Inverting Adversarially Robust Networks for Image Synthesis. CoRR abs/2106.06927 (2021) - [i14]Iou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing:
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning. CoRR abs/2107.11444 (2021) - [i13]Iou-Jen Liu, Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing:
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning. CoRR abs/2108.03319 (2021) - [i12]Qian Jiang, Xiaofan Zhang, Deming Chen, Minh N. Do, Raymond A. Yeh:
EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search. CoRR abs/2111.12299 (2021) - 2020
- [c13]Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing:
High-Throughput Synchronous Deep RL. NeurIPS 2020 - [c12]Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing:
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning. NeurIPS 2020 - [i11]Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing:
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning. CoRR abs/2007.01293 (2020) - [i10]Junzhe Zhu, Raymond A. Yeh, Mark Hasegawa-Johnson:
Multi-Decoder DPRNN: High Accuracy Source Counting and Separation. CoRR abs/2011.12022 (2020) - [i9]Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing:
High-Throughput Synchronous Deep RL. CoRR abs/2012.09849 (2020)
2010 – 2019
- 2019
- [c11]Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing:
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning. CoRL 2019: 590-602 - [c10]Raymond A. Yeh, Alexander G. Schwing, Jonathan Huang, Kevin Murphy:
Diverse Generation for Multi-Agent Sports Games. CVPR 2019: 4610-4619 - [c9]Khoi-Nguyen C. Mac, Dhiraj Joshi, Raymond A. Yeh, Jinjun Xiong, Rogério Schmidt Feris, Minh N. Do:
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection. ICCV 2019: 6281-6290 - [c8]Raymond A. Yeh, Yuan-Ting Hu, Alexander G. Schwing:
Chirality Nets for Human Pose Regression. NeurIPS 2019: 8161-8171 - [i8]Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing:
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning. CoRR abs/1911.00025 (2019) - [i7]Raymond A. Yeh, Yuan-Ting Hu, Alexander G. Schwing:
Chirality Nets for Human Pose Regression. CoRR abs/1911.00029 (2019) - 2018
- [c7]Raymond A. Yeh, Minh N. Do, Alexander G. Schwing:
Unsupervised Textual Grounding: Linking Words to Image Concepts. CVPR 2018: 6125-6134 - [c6]Teck-Yian Lim, Raymond A. Yeh, Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson:
Time-Frequency Networks for Audio Super-Resolution. ICASSP 2018: 646-650 - [c5]Raymond A. Yeh, Teck-Yian Lim, Chen Chen, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do:
Image Restoration with Deep Generative Models. ICASSP 2018: 6772-6776 - [i6]Raymond A. Yeh, Minh N. Do, Alexander G. Schwing:
Unsupervised Textual Grounding: Linking Words to Image Concepts. CoRR abs/1803.11185 (2018) - [i5]Raymond A. Yeh, Jinjun Xiong, Wen-mei W. Hwu, Minh N. Do, Alexander G. Schwing:
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts. CoRR abs/1803.11209 (2018) - [i4]Khoi-Nguyen C. Mac, Dhiraj Joshi, Raymond A. Yeh, Jinjun Xiong, Rogério Schmidt Feris, Minh N. Do:
Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection. CoRR abs/1811.08815 (2018) - 2017
- [c4]Raymond A. Yeh, Chen Chen, Teck-Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do:
Semantic Image Inpainting with Deep Generative Models. CVPR 2017: 6882-6890 - [c3]Ziwei Liu, Raymond A. Yeh, Xiaoou Tang, Yiming Liu, Aseem Agarwala:
Video Frame Synthesis Using Deep Voxel Flow. ICCV 2017: 4473-4481 - [c2]Raymond A. Yeh, Jinjun Xiong, Wen-Mei W. Hwu, Minh N. Do, Alexander G. Schwing:
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts. NIPS 2017: 1912-1922 - [i3]Ziwei Liu, Raymond A. Yeh, Xiaoou Tang, Yiming Liu, Aseem Agarwala:
Video Frame Synthesis using Deep Voxel Flow. CoRR abs/1702.02463 (2017) - 2016
- [c1]Raymond A. Yeh, Mark Hasegawa-Johnson, Minh N. Do:
Stable and symmetric filter convolutional neural network. ICASSP 2016: 2652-2656 - [i2]Raymond A. Yeh, Chen Chen, Teck-Yian Lim, Mark Hasegawa-Johnson, Minh N. Do:
Semantic Image Inpainting with Perceptual and Contextual Losses. CoRR abs/1607.07539 (2016) - [i1]Raymond A. Yeh, Ziwei Liu, Dan B. Goldman, Aseem Agarwala:
Semantic Facial Expression Editing using Autoencoded Flow. CoRR abs/1611.09961 (2016)
Coauthor Index
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