2 citations · 3 across the 7 of their papers we have counts for
7 papers · 1 filter
VLM-Guided Group Preference Alignment for Diffusion-based Human Mesh Recovery
Wenhao Shen, Hao Wang, Wanqi Yin +5
Human mesh recovery (HMR) from a single RGB image is inherently ambiguous, as multiple 3D poses can correspond to the same 2D observation. Recent diffusion-based methods tackle thi…
Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation
Lechun You, Zhonghua Wu, Weide Liu +5
Current methods for 3D semantic segmentation propose training models with limited annotations to address the difficulty of annotating large, irregular, and unordered 3D point cloud…
OccLE: Label-Efficient 3D Semantic Occupancy Prediction
Naiyu Fang, Zheyuan Zhou, Fayao Liu +5
3D semantic occupancy prediction offers an intuitive and efficient scene understanding and has attracted significant interest in autonomous driving perception. Existing approaches…
Gaussian Mixture based Evidential Learning for Stereo Matching
Weide Liu, Xingxing Wang, Lu Wang +3
In this paper, we introduce a novel Gaussian mixture based evidential learning solution for robust stereo matching. Diverging from previous evidential deep learning approaches that…
Text-to-Image Rectified Flow as Plug-and-Play Priors
Xiaofeng Yang, Cheng Chen, Xulei Yang +2
Large-scale diffusion models have achieved remarkable performance in generative tasks. Beyond their initial training applications, these models have proven their ability to functio…
Sync4D: Video Guided Controllable Dynamics for Physics-Based 4D Generation
Zhoujie Fu, Jiacheng Wei, Wenhao Shen +5
In this work, we introduce a novel approach for creating controllable dynamics in 3D-generated Gaussians using casually captured reference videos. Our method transfers the motion o…
Learn to Optimize Denoising Scores for 3D Generation: A Unified and Improved Diffusion Prior on NeRF and 3D Gaussian Splatting
Xiaofeng Yang, Yiwen Chen, Cheng Chen +5
We propose a unified framework aimed at enhancing the diffusion priors for 3D generation tasks. Despite the critical importance of these tasks, existing methodologies often struggl…