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20242026
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cs.CV2026

COVTrack++: Learning Open-Vocabulary Multi-Object Tracking from Continuous Videos via a Synergistic Paradigm

Zekun Qian, Wei Feng, Ruize Han +1

Multi-Object Tracking (MOT) has traditionally focused on a few specific categories, restricting its applicability to real-world scenarios involving diverse objects. Open-Vocabulary…

cs.CV2025

PVNet: Point-Voxel Interaction LiDAR Scene Upsampling Via Diffusion Models

Xianjing Cheng, Lintai Wu, Zuowen Wang +3

Accurate 3D scene understanding in outdoor environments heavily relies on high-quality point clouds. However, LiDAR-scanned data often suffer from extreme sparsity, severely hinder…

cs.CV2025

Unsupervised 3D Point Cloud Completion via Multi-view Adversarial Learning

Lintai Wu, Xianjing Cheng, Yong Xu +2

In real-world scenarios, scanned point clouds are often incomplete due to occlusion issues. The tasks of self-supervised and weakly-supervised point cloud completion involve recons…

cs.CV2025

Synthetic-To-Real Video Person Re-ID

Xiangqun Zhang, Wei Feng, Ruize Han +3

Person re-identification (Re-ID) is an important task and has significant applications for public security and information forensics, which has progressed rapidly with the developm…

cs.CV2024

VOVTrack: Exploring the Potentiality in Videos for Open-Vocabulary Object Tracking

Zekun Qian, Ruize Han, Junhui Hou +2

Open-vocabulary multi-object tracking (OVMOT) represents a critical new challenge involving the detection and tracking of diverse object categories in videos, encompassing both see…