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cs.CV2025
Selecting and Pruning: A Differentiable Causal Sequentialized State-Space Model for Two-View Correspondence Learning
Xiang Fang, Shihua Zhang, Hao Zhang +3
Two-view correspondence learning aims to discern true and false correspondences between image pairs by recognizing their underlying different information. Previous methods either t…
cs.CV2024
3D Lane Detection from Front or Surround-View using Joint-Modeling & Matching
Haibin Zhou, Huabing Zhou, Jun Chang +2
3D lanes offer a more comprehensive understanding of the road surface geometry than 2D lanes, thereby providing crucial references for driving decisions and trajectory planning. Wh…