most citedAdaptive Margin Contrastive Learning for Ambiguity-aware 3D Semantic Segmentation

4 citations · 4 across the 5 of their papers we have counts for

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cs.CV2026

Boundary Voting Network for Ambiguity-Aware Timestamp-Supervised Action Segmentation

Runzhong Zhang, Yueqi Duan, Yang Chen +4

Timestamp-supervised action segmentation aims to segment and classify actions in untrimmed videos with a random frame annotated per action. Precisely localizing action boundaries f…

cs.CV2026

ReplicateAnyScene: Zero-Shot Video-to-3D Composition via Textual-Visual-Spatial Alignment

Mingyu Dong, Chong Xia, Mingyuan Jia +4

Humans exhibit an innate capacity to rapidly perceive and segment objects from video observations, and even mentally assemble them into structured 3D scenes. Replicating such capab…

cs.CV2026

Spectral Defense Against Resource-Targeting Attack in 3D Gaussian Splatting

Yang Chen, Yi Yu, Jiaming He +3

Recent advances in 3D Gaussian Splatting (3DGS) deliver high-quality rendering, yet the Gaussian representation exposes a new attack surface, the resource-targeting attack. This at…

cs.CV2025

Learning Efficient and Generalizable Human Representation with Human Gaussian Model

Yifan Liu, Shengjun Zhang, Chensheng Dai +4

Modeling animatable human avatars from videos is a long-standing and challenging problem. While conventional methods require per-instance optimization, recent feed-forward methods…

cs.CV2025

Ambiguity-aware Point Cloud Segmentation by Adaptive Margin Contrastive Learning

Yang Chen, Yueqi Duan, Haowen Sun +2

This paper proposes an adaptive margin contrastive learning method for 3D semantic segmentation on point clouds. Most existing methods use equally penalized objectives, which ignor…

cs.CV2025

PointVDP: Learning View-Dependent Projection by Fireworks Rays for 3D Point Cloud Segmentation

Yang Chen, Yueqi Duan, Haowen Sun +3

In this paper, we propose view-dependent projection (VDP) to facilitate point cloud segmentation, designing efficient 3D-to-2D mapping that dynamically adapts to the spatial geomet…