Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation
Haochen Wang*,
Xiaodan Du*,
Jiahao Li*,
Raymond A. Yeh,
Greg Shakhnarovich
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
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Tree Instance Segmentation using Temporal Structured Images
Adnan Firoze,
Cameron Wingren,
Raymond A. Yeh,
Bedrich Benes,
Daniel Aliaga
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
GeoCode: Interpretable Shape Programs
Ofek Pearl,
Itai Lang,
Yuhua Hu,
Raymond A. Yeh,
Rana Hanocka
arXiv preprint, 2022
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Code
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks
Renan A. Rojas-Gomez,
Teck-Yian Lim,
Alexander G. Schwing,
Minh N. Do,
Raymond A. Yeh
Neural Information Processing Systems (NeurIPS), 2022
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Code
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation
William M Gao,
April Wang,
Gal Metzer,
Raymond A. Yeh,
Rana Hanocka
British Machine Vision Conference (BMVC), 2022
Oral Presentation
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Inverting Adversarially Robust Networks for Image Synthesis
Renan A. Rojas-Gomez,
Raymond A. Yeh,
Minh N Do,
Anh Nguyen
Asian Conference on Computer Vision (ACCV), 2022
PDF
Text-Free Learning of a Natural Language Interface for Pretrained Face Generators
Xiaodan Du,
Raymond A. Yeh,
Nicholas Kolkin,
Eli Shechtman,
Greg Shakhnarovich
arXiv preprint, 2022
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Adapting CLIP For Phrase Localization Without Further Training
Jiahao Li,
Greg Shakhnarovich,
Raymond A. Yeh
arXiv preprint, 2022
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Code
Total Variation Optimization Layers for Computer Vision
Raymond A. Yeh,
Yuan-Ting Hu,
Zhongzheng Ren,
Alexander G. Schwing
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
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Code
Equivariance Discovery by Learned Parameter-Sharing
Raymond A. Yeh,
Yuan-Ting Hu,
Mark Hasegawa-Johnson,
Alexander G. Schwing
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
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Code
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning
Iou-Jen Liu*,
Zhongzheng Ren*,
Raymond A. Yeh*,
Alexander G. Schwing
International Conference on Intelligent Robots and Systems (IROS), 2021
Also presented at Reinforcement Learning for Real Life Workshop at ICML, 2021
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Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu,
Unnat Jain,
Raymond A. Yeh,
Alexander G. Schwing
International Conference on Machine Learning (ICML), 2021
Long Talk
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SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data
Yuan-Ting Hu,
Jiahong Wang,
Raymond A. Yeh,
Alexander G. Schwing
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Oral Presentation
PDF
Project
MULTI-DECODER DPRNN: Source Separation for Variable Number of Speakers
Junzhe Zhu,
Raymond A. Yeh,
Mark Hasegawa-Johnson
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
PDF
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning
Zhongzheng Ren*,
Raymond A. Yeh*,
Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2020
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Code
High-Throughput Synchronous Deep Reinforcement Learning
Iou-Jen Liu,
Raymond A. Yeh,
Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2020
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Code
Chirality Nets for Human Pose Regression
Raymond A. Yeh*,
Yuan-Ting Hu*,
Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2019
Also presented at Sets & Paritions Workshop
Contributed Talk
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PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu*,
Raymond A. Yeh*,
Alexander G. Schwing
Conference on Robot Learning (CoRL), 2019
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Code
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection
Khoi-Nguyen C. Mac,
Dhiraj Joshi,
Raymond A. Yeh,
Jinjun Xiong,
Rogerio S. Feris,
Minh N. Do
International Conference on Computer Vision (ICCV), 2019
Oral Presentation
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Diverse Generation for Multi-agent Sports Games
Raymond A. Yeh,
Alexander G. Schwing,
Jonathan Huang,
Kevin Murphy
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Oral Presentation
PDF
Project
Unsupervised Textual Grounding: Linking Words to Image Concepts
Raymond A. Yeh,
Minh N. Do,
Alexander G. Schwing
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Spotlight Presentation
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Project
Time-Frequency Networks for Audio Super-Resolution
Teck Yian Lim*,
Raymond A. Yeh*,
Yijia Xu,
Minh N. Do,
Mark Hasegawa-Johnson
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
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Code
Image Restoration with Deep Generative Models
Raymond A. Yeh*,
Teck Yian Lim*,
Chen Chen,
Alexander G. Schwing,
Mark Hasegawa-Johnson,
Minh N. Do
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
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Project
Code
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Raymond A. Yeh,
Jinjun Xiong,
Wen-mei W. Hwu,
Minh N. Do,
Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2017
Oral Presentation
PDF
Project
Video Frame Synthesis using Deep Voxel Flow
Ziwei Liu,
Raymond A. Yeh,
Xiaoou Tang,
Yiming Liu,
Aseem Agarwala
International Conference on Computer Vision (ICCV), 2017
Oral Presentation
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Project
Code
Semantic Image Inpainting with Deep Generative Models
Raymond A. Yeh*,
Chen Chen*,
Teck Yian Lim,
Alexander G. Schwing,
Mark Hasegawa-Johnson,
Minh N. Do
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
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Project
Code
Semantic Facial Expression Editing using Autoencoded Flow
Raymond A. Yeh,
Ziwei Liu,
Dan B Goldman,
Aseem Agarwala
arXiv preprint, 2016
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Stable and Symmetric Filter Convolutional Neural Network
Raymond Yeh,
Mark Hasegawa-Johnson,
Minh N. Do
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2016
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