collaborators

7 papers

cs.CV2026

GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking

Shiyang Liu, Weiquan Lin, Luping Xiao +4

Prior-free 6D object pose tracking seeks to recover the trajectory of an unseen object from a single RGB video without object-specific CAD models, posed reference images, or pose a…

cs.CV2026

Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfer

Weiquan Lin, Yu Deng, Shiyang Liu +6

Hand-object interaction (HOI) modeling remains challenging because it requires joint reasoning about hand articulation, object geometry, contact, semantics, and dynamics under seve…

cs.RO2026

HumanoidArena: Benchmarking Egocentric Hierarchical Whole-body Learning

Taowen Wang, Zikang Xie, Bin Yang +13

Humanoid robots promise whole-body interaction in human-centered environments, but scalable policy learning remains difficult because task-level decision-making and whole-body dyna…

cs.CV2026

ScaleHP: Scale-Mediated Optimization of Coupled Errors for Metric-Space Hand Pose Estimation

Ruitao Jing, Xingyu Chen, Hongyang Li +3

In this paper, we present ScaleHP, a unified framework that explicitly represents per-instance metric scale to resolve the coupled errors in calibrated camera-space hand pose estim…

cs.CV2025

SceneMaker: Open-set 3D Scene Generation with Decoupled De-occlusion and Pose Estimation Model

Yukai Shi, Weiyu Li, Zihao Wang +4

We propose a decoupled 3D scene generation framework called SceneMaker in this work. Due to the lack of sufficient open-set de-occlusion and pose estimation priors, existing method…

cs.CV2025

Detect Anything via Next Point Prediction

Qing Jiang, Junan Huo, Xingyu Chen +6

Object detection has long been dominated by traditional coordinate regression-based models, such as YOLO, DETR, and Grounding DINO. Although recent efforts have attempted to levera…

cs.CV2025

SegDINO3D: 3D Instance Segmentation Empowered by Both Image-Level and Object-Level 2D Features

Jinyuan Qu, Hongyang Li, Xingyu Chen +5

In this paper, we present SegDINO3D, a novel Transformer encoder-decoder framework for 3D instance segmentation. As 3D training data is generally not as sufficient as 2D training i…