3 papers
cs.CV2025
Propagating Sparse Depth via Depth Foundation Model for Out-of-Distribution Depth Completion
Shenglun Chen, Xinzhu Ma, Hong Zhang +2
Depth completion is a pivotal challenge in computer vision, aiming at reconstructing the dense depth map from a sparse one, typically with a paired RGB image. Existing learning bas…
cs.CV2024
Is a Pure Transformer Effective for Separated and Online Multi-Object Tracking?
Chongwei Liu, Haojie Li, Zhihui Wang +1
Recent advances in Multi-Object Tracking (MOT) have demonstrated significant success in short-term association within the separated tracking-by-detection online paradigm. However,…
cs.CV2024
Learning Pixel-wise Continuous Depth Representation via Clustering for Depth Completion
Chen Shenglun, Zhang Hong, Ma XinZhu +2
Depth completion is a long-standing challenge in computer vision, where classification-based methods have made tremendous progress in recent years. However, most existing classific…