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arXiv AI By Qi Xiong, Qinghua Zhao, Yongqiang Xi

E3tereo: Improving Stereo Matching at Depth Boundaries with Learned Geometric Edges

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E3Stereo improves stereo matching at depth boundaries by learning geometric edges from disparity supervision. It integrates these edges with backbone disparity and image details to predict full‑resolution disparity corrections, emphasizing boundary errors during training. On the Scene Flow dataset, E3Stereo reduces end‑point error at depth boundaries by 9.5%–14.3% across multiple models and improves all eleven metrics on ETH3D, KITTI 2012, and KITTI 2015 after fine‑tuning.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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