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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

MonoDream: Monocular Vision-Language Navigation with Panoramic Dreaming

Shuo Wang, Yongcai Wang, Zhaoxin Fan +8

Vision-Language Navigation (VLN) tasks often leverage panoramic RGB and depth inputs to provide rich spatial cues for action planning, but these sensors can be costly or less acces…

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.CV2025

Point-Cache: Test-time Dynamic and Hierarchical Cache for Robust and Generalizable Point Cloud Analysis

Hongyu Sun, Qiuhong Ke, Ming Cheng +4

This paper proposes a general solution to enable point cloud recognition models to handle distribution shifts at test time. Unlike prior methods, which rely heavily on training dat…