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cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…