4 papers · 1 filter
RoSe: Robust Self-supervised Stereo Matching under Adverse Weather Conditions
Yun Wang, Junjie Hu, Junhui Hou +3
Recent self-supervised stereo matching methods have made significant progress, but their performance significantly degrades under adverse weather conditions such as night, rain, an…
Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration
Yifan Zhang, Junhui Hou, Siyu Ren +3
This paper introduces a novel self-supervised learning framework for enhancing 3D perception in autonomous driving scenes. Specifically, our approach, namely NCLR, focuses on 2D-3D…
CFTrack: Enhancing Lightweight Visual Tracking through Contrastive Learning and Feature Matching
Juntao Liang, Jun Hou, Weijun Zhang +1
Achieving both efficiency and strong discriminative ability in lightweight visual tracking is a challenge, especially on mobile and edge devices with limited computational resource…
Fine-grained Image-to-LiDAR Contrastive Distillation with Visual Foundation Models
Yifan Zhang, Junhui Hou
Contrastive image-to-LiDAR knowledge transfer, commonly used for learning 3D representations with synchronized images and point clouds, often faces a self-conflict dilemma. This is…