activity
20202026
most citedNeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

85 citations · 238 across the 41 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

TrackFish3D: Self-Supervised 3D Tracking of Schooling Fish from Multi-view Videos

Patt Phurtivilai, Zhiyang Dou, Yifan Wu +5

Quantifying collective fish behavior requires accurate trajectories, yet multi-view 3D tracking remains challenging due to frequent occlusions, visually similar individuals, and th…

cs.GR2026

MoSAT: Human Motion Generation from Spatial Audio and Textual Description

Shuyang Xu, Zhiyang Dou, Yiduo Hao +8

Human motion is shaped by both external acoustic events and behavioral intent: spatial audio conveys environmental cues that elicit or guide a response, while text specifies the de…

cs.GR2026

SAND: Spatially Adaptive Network Depth for Fast Sampling of Neural Implicit Surfaces

Chuanxiang Yang, Junhui Hou, Yuan Liu +5

Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of network evaluations. We observe that…

cs.CV2026

UNIC: Neural Garment Deformation Field for Real-time Clothed Character Animation

Chengfeng Zhao, Junbo Qi, Yulou Liu +6

Simulating physically realistic garment deformations is an essential task for virtual immersive experience, which is often achieved by physics simulation methods. However, these me…

cs.CV2026

BuildAnyPoint: 3D Building Structured Abstraction from Diverse Point Clouds

Tongyan Hua, Haoran Gong, Yuan Liu +3

We introduce BuildAnyPoint, a novel generative framework for structured 3D building reconstruction from point clouds with diverse distributions, such as those captured by airborne…

cs.CV2026

EgoReAct: Egocentric Video-Driven 3D Human Reaction Generation

Libo Zhang, Zekun Li, Tianyu Li +10

Humans exhibit adaptive, context-sensitive responses to egocentric visual input. However, faithfully modeling such reactions from egocentric video remains challenging due to the du…