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cs.CV2026

UECP: Uncertainty-Enhanced Collaborative Perception

Kang Yang, Tianci Bu, Peng Wang +3

Collaborative perception serves as a pivotal solution to enhance the perception capability of individual agents in autonomous driving, where a core challenge lies in seeking reliab…

cs.CV2026

BOLT: Online Lightweight Adaptation for Preparation-Free Heterogeneous Cooperative Perception

Kang Yang, Tianci Bu, Peng Wang +2

Most existing heterogeneous cooperative perception methods depend on prior preparation like offline joint training or tailored collaborator-model adaptation. Such preprocessing is,…

cs.CV2026

EIMC: Efficient Instance-aware Multi-modal Collaborative Perception

Kang Yang, Peng Wang, Lantao Li +4

Multi-modal collaborative perception calls for great attention to enhancing the safety of autonomous driving. However, current multi-modal approaches remain a ``local fusion to com…

cs.CV2025

Mem4D: Decoupling Static and Dynamic Memory for Dynamic Scene Reconstruction

Xudong Cai, Shuo Wang, Peng Wang +7

Reconstructing dense geometry for dynamic scenes from a monocular video is a critical yet challenging task. Recent memory-based methods enable efficient online reconstruction, but…

cs.CV2024

VSFormer: Mining Correlations in Flexible View Set for Multi-view 3D Shape Understanding

Hongyu Sun, Yongcai Wang, Peng Wang +3

View-based methods have demonstrated promising performance in 3D shape understanding. However, they tend to make strong assumptions about the relations between views or learn the m…

cs.CV2024

DroneMOT: Drone-based Multi-Object Tracking Considering Detection Difficulties and Simultaneous Moving of Drones and Objects

Peng Wang, Yongcai Wang, Deying Li

Multi-object tracking (MOT) on static platforms, such as by surveillance cameras, has achieved significant progress, with various paradigms providing attractive performances. Howev…