2 citations · 5 across the 10 of their papers we have counts for
6 papers · 1 filter
Open-CHOIR: Open-World Contact-Aware 4D Hand-Object Interaction Reconstruction
Hao Xu, Yilin Liu, Yinqiao Wang +2
We ask whether everyday open-world monocular videos can be turned into reusable 4D interaction primitives: articulated hand motion, object shape with 6D pose over time, and the whe…
EgoHandICL: Egocentric 3D Hand Reconstruction with In-Context Learning
Binzhu Xie, Shi Qiu, Sicheng Zhang +5
Robust 3D hand reconstruction in egocentric vision is challenging due to depth ambiguity, self-occlusion, and complex hand-object interactions. Prior methods mitigate these issues…
HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving
R. D. Lin, Pengcheng Weng, Yinqiao Wang +3
LiDAR point cloud semantic segmentation plays a crucial role in autonomous driving. In recent years, semi-supervised methods have gained popularity due to their significant reducti…
UniHOPE: A Unified Approach for Hand-Only and Hand-Object Pose Estimation
Yinqiao Wang, Hao Xu, Pheng-Ann Heng +1
Estimating the 3D pose of hand and potential hand-held object from monocular images is a longstanding challenge. Yet, existing methods are specialized, focusing on either bare-hand…
HandBooster: Boosting 3D Hand-Mesh Reconstruction by Conditional Synthesis and Sampling of Hand-Object Interactions
Hao Xu, Haipeng Li, Yinqiao Wang +2
Reconstructing 3D hand mesh robustly from a single image is very challenging, due to the lack of diversity in existing real-world datasets. While data synthesis helps relieve the i…
SiMA-Hand: Boosting 3D Hand-Mesh Reconstruction by Single-to-Multi-View Adaptation
Yinqiao Wang, Hao Xu, Pheng-Ann Heng +1
Estimating 3D hand mesh from RGB images is a longstanding track, in which occlusion is one of the most challenging problems. Existing attempts towards this task often fail when the…