* Equal contribution
† Corresponding author
OV9D: Open-Vocabulary Category-Level 9D Object Pose and Size Estimation. RAL 2024.
Freditor: High-Fidelity and Transferable NeRF Editing by Frequency Decomposition. ECCV 2024.
An Optimization Framework to Enforce Multi-View Consistency for Texturing 3D Meshes Using Pre-Trained Text-2-Image Models. ECCV 2024.
High-Fidelity 3D Textured Shapes Generation by Sparse Encoding and Adversarial Decoding. ECCV 2024.
Implicit Field Learning with Point Diffusion for Generalizable 3D Object Reconstruction from Single RGB-D Images. CVPR 2024, Highlight.
RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D. CVPR 2024, Highlight.
GPLD3D: Latent Diffusion of 3D Shape Generative Models by Enforcing Geometric and Physical Priors. CVPR 2024, Oral.
Weihao Yuan, Xiaodong Gu, Heng Li, Zilong Dong, Siyu Zhu, “3D Former: Monocular Scene Reconstruction with 3D SDF Transformers“, International Conference on Learning Representations (ICLR). 2023.
Heng Li, Xiaodong Gu, Weihao Yuan, Luwei Yang, Zilong Dong, Ping Tan, “Dense RGB SLAM with Neural Implicit Maps“, International Conference on Learning Representations (ICLR). 2023.
Weihao Yuan, Xiaodong Gu, Zuozhuo Dai, Siyu Zhu, Ping Tan, “NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2022.
Xiaodong Gu, Chengzhou Tang, Weihao Yuan, Zuozhuo Dai, Siyu Zhu, Ping Tan, “RCP: Recurrent Closest Point for Scene Flow Estimation on 3D Point Clouds”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2022. Oral Presentation.
Xiaodong Gu*, Weihao Yuan*†, Zuozhuo Dai, Chengzhou Tang, Siyu Zhu, Ping Tan, “DRO: Deep Recurrent Optimizer for Structure-from-Motion”. IEEE Robotics and Automation Letters (RA-L). 2023.
Zuozhuo Dai, Guangyuan Wang, Weihao Yuan, Siyu Zhu, Ping Tan, “Cluster Contrast for Unsupervised Person Re-Identification”, Asian Conference on Computer Vision (ACCV). IEEE, 2022.
Weihao Yuan, Yazhan Zhang, Bingkun Wu, Michael Yu Wang, Qifeng Chen, “Stereo Matching by Self-supervision of Multiscopic Vision”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021.
Weihao Yuan, Michael Yu Wang, Qifeng Chen, “Self-supervised Object Tracking with Cycle-consistent Siamese Networks”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020.
Haoran Song, Joshua A Haustein, Weihao Yuan, Kaiyu Hang, Michael Yu Wang, Danica Kragic, Johannes A Stork, “Multi-Object Rearrangement with Monte Carlo Tree Search: A Case Study on Planar Nonprehensile Sorting”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020.
Weihao Yuan, Rui Fan, Michael Yu Wang, Qifeng Chen, “MFuseNet: Robust Depth Estimation with Learned Multiscopic Fusion”, IEEE International Conference on Robotics and Automation (ICRA), published in IEEE Robotics and Automation Letters (RA-L), 5(2): 3113-3120, 2020.
Yazhan Zhang, Weihao Yuan, Zicheng Kan, Michael Yu Wang, “Toward Learning to Detect and Predict Contact Events on Vision-based Tactile Sensor”, Conference on Robot Learning (CoRL). 2019. Oral presentation.
Weihao Yuan, Kaiyu Hang, Danica Kragic, Michael Yu Wang, Johannes A. Stork, “End-to-End Nonprehensile Rearrangement with Deep Reinforcement Learning and Simulation-to-Reality Transfer”, Robotics and Autonomous Systems (RAS), 119: 119-134, 2019.
Weihao Yuan, Kaiyu Hang, Haoran Song, Danica Kragic, Michael Yu Wang, Johannes A. Stork, “Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation”, in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 2153-2160. IEEE, 2019.
Weihao Yuan, Johannes Andreas Stork, Danica Kragic, Michael Yu Wang, Kaiyu Hang, “Rearrangement with Nonprehensile Manipulation Using Deep Reinforcement Learning”, in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 270-277. IEEE, 2018.