collaborators

7 papers

cs.CV2026

StableHand: Quality-Aware Flow Matching for World-Space Dual-Hand Motion Estimation from Egocentric Video

Huajian Zeng, Chaohua Yao, Yuantai Zhang +3

Recovering world space 4D motion of two interacting hands from egocentric video is a fundamental capability for supervising robot policy learning, where wrist trajectories track th…

cs.RO2026

Efficient Feature-Free Initialization for Monocular Visual-Inertial Systems Using a Feed-Forward 3D Model

Yuantai Zhang, Jiaqi Yang, Huajian Zeng +5

Fast and reliable initialization is critical for monocular visual-inertial navigation systems (VINS), as it establishes the starting conditions for subsequent state estimation. Des…

cs.CV2026

EgoFlow: Gradient-Guided Flow Matching for Egocentric 6DoF Object Motion Generation

Abhishek Saroha, Huajian Zeng, Xingxing Zuo +2

Understanding and predicting object motion from egocentric video is fundamental to embodied perception and interaction. However, generating physically consistent 6DoF trajectories…

cs.CV2026

GMT: Goal-Conditioned Multimodal Transformer for 6-DOF Object Trajectory Synthesis in 3D Scenes

Huajian Zeng, Abhishek Saroha, Daniel Cremers +1

Synthesizing controllable 6-DOF object manipulation trajectories in 3D environments is essential for enabling robots to interact with complex scenes, yet remains challenging due to…

cs.RO2026

ClearDepth: Enhanced Stereo Perception of Transparent Objects for Robotic Manipulation

Kaixin Bai, Huajian Zeng, Lei Zhang +4

Transparent object depth perception poses a challenge in everyday life and logistics, primarily due to the inability of standard 3D sensors to accurately capture depth on transpare…

cs.RO2026

FlowHOI: Flow-based Semantics-Grounded Generation of Hand-Object Interactions for Dexterous Robot Manipulation

Huajian Zeng, Lingyun Chen, Jiaqi Yang +4

Recent vision-language-action (VLA) models can generate plausible end-effector motions, yet they often fail in long-horizon, contact-rich tasks because the underlying hand-object i…