papers

Publications (9)

cs.CV2023

ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction

Zhengdi Yu, Shaoli Huang, Chen Fang +2

Reconstructing two hands from monocular RGB images is challenging due to frequent occlusion and mutual confusion. Existing methods mainly learn an entangled representation to encod…

cs.CV2021

P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching

Bing Wang, Changhao Chen, Zhaopeng Cui +8

Accurately describing and detecting 2D and 3D keypoints is crucial to establishing correspondences across images and point clouds. Despite a plethora of learning-based 2D or 3D loc…

cs.CV2025

Towards Dynamic 3D Reconstruction of Hand-Instrument Interaction in Ophthalmic Surgery

Ming Hu, Zhengdi Yu, Feilong Tang +7

Accurate 3D reconstruction of hands and instruments is critical for vision-based analysis of ophthalmic microsurgery, yet progress has been hampered by the lack of realistic, large…

cs.CV2025

Geometric Neural Distance Fields for Learning Human Motion Priors

Zhengdi Yu, Simone Foti, Linguang Zhang +4

We introduce Neural Riemannian Motion Fields (NRMF), a novel 3D generative human motion prior that enables robust, temporally consistent, and physically plausible 3D motion recover…

cs.CV2025

Dyn-HaMR: Recovering 4D Interacting Hand Motion from a Dynamic Camera

Zhengdi Yu, Stefanos Zafeiriou, Tolga Birdal

We propose Dyn-HaMR, to the best of our knowledge, the first approach to reconstruct 4D global hand motion from monocular videos recorded by dynamic cameras in the wild. Reconstruc…

cs.CV2024

SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark

Zhengdi Yu, Shaoli Huang, Yongkang Cheng +1

We present SignAvatars, the first large-scale, multi-prompt 3D sign language (SL) motion dataset designed to bridge the communication gap for Deaf and hard-of-hearing individuals.…

cs.CV2023

U3DS: Unsupervised 3D Semantic Scene Segmentation

Jiaxu Liu, Zhengdi Yu, Toby P. Breckon +1

Contemporary point cloud segmentation approaches largely rely on richly annotated 3D training data. However, it is both time-consuming and challenging to obtain consistently accura…

cs.CV2023

Decomposed Human Motion Prior for Video Pose Estimation via Adversarial Training

Wenshuo Chen, Xiang Zhou, Zhengdi Yu +2

Estimating human pose from video is a task that receives considerable attention due to its applicability in numerous 3D fields. The complexity of prior knowledge of human body move…

cs.CV2022

RangeUDF: Semantic Surface Reconstruction from 3D Point Clouds

Bing Wang, Zhengdi Yu, Bo Yang +5

We present RangeUDF, a new implicit representation based framework to recover the geometry and semantics of continuous 3D scene surfaces from point clouds. Unlike occupancy fields…