Multi-Object 3D Grounding with Dynamic Modules and Language Informed Spatial Attention
Haomeng Zhang,
Chiao-An Yang,
Raymond A. Yeh
Neural Information Processing Systems (NeurIPS), 2024
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
Md Ashiqur Rahman,
Robert J. George,
Mogab Elleithy,
Daniel Leibovici,
Zongyi Li,
Boris Bonev,
Colin White,
Julius Berner,
Raymond A. Yeh,
Jean Kossaifi,
Kamyar Azizzadenesheli,
Anima Anandkumar
Neural Information Processing Systems (NeurIPS), 2024
PDF
Code
IMMA: Immunizing text-to-image Models against Malicious Adaptation
Amber Yijia Zheng,
Raymond A. Yeh
European Conference on Computer Vision (ECCV), 2024
Best Paper Runner-up at AI4CC in CVPR Workshop 2024
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Code
Learning to Obstruct Few-Shot Image Classification over Restricted Classes
Amber Yijia Zheng*,
Chiao-An Yang*,
Raymond A. Yeh
European Conference on Computer Vision (ECCV), 2024
PDF
Project
Code
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-Time
Chiao-An Yang,
Ziwei Liu,
Raymond A. Yeh
European Conference on Computer Vision (ECCV), 2024
PDF
Code
Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors
Jae Joong Lee,
Bosheng Li,
Sara Beery,
Jonathan Huang,
Songlin Fei,
Raymond A. Yeh ,
Bedrich Benes
European Conference on Computer Vision (ECCV), 2024
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Project
Code
Making Vision Transformers Truly Shift-Equivariant
Renan A. Rojas-Gomez,
Teck-Yian Lim,
Minh N. Do,
Raymond A. Yeh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
PDF
Project
Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in a Neural Radiance Field
Joshua Ahn*,
Haochen Wang*,
Raymond A. Yeh,
Greg Shakhnarovich
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
PDF
Project
AmbiGen: Generating Ambigrams from Pre-trained Diffusion Model
Boheng Zhao,
Rana Hanocka,
Raymond A. Yeh
CVPR Workshop on Graphic Design Understanding and Generation, 2024
PDF
Project
Truly Scale-Equivariant Deep Nets with Fourier Layers
Md Ashiqur Rahman,
Raymond A. Yeh
Neural Information Processing Systems (NeurIPS), 2023
PDF
Project
Code
Surface Snapping Optimization Layer for Single Image Object Shape Reconstruction
Yuan-Ting Hu,
Alexander G. Schwing,
Raymond A. Yeh
International Conference on Machine Learning (ICML), 2023
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Project
Code
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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Project
Code
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
PDF
Project
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
PDF
Project
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
PDF
Project
Code
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
Code
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
PDF
Code
Adapting CLIP For Phrase Localization Without Further Training
Jiahao Li,
Greg Shakhnarovich,
Raymond A. Yeh
arXiv preprint, 2022
PDF
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
PDF
Project
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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Project
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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Project
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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Project
Code
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
PDF
Project
Code
High-Throughput Synchronous Deep Reinforcement Learning
Iou-Jen Liu,
Raymond A. Yeh,
Alexander G. Schwing
Neural Information Processing Systems (NeurIPS), 2020
PDF
Project
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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Project
Code
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
PDF
Project
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
PDF
Project
Code
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
PDF
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
PDF
Project
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
PDF
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
PDF
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
PDF
Project
Code
Semantic Facial Expression Editing using Autoencoded Flow
Raymond A. Yeh,
Ziwei Liu,
Dan B Goldman,
Aseem Agarwala
arXiv preprint, 2016
PDF
Project
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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Project