A semi-supervised RGB-D scene parsing framework using patch swapping between RGB and depth, lightweight depth feature injection, and depth-derived boundary supervision reports state-of-the-art results on NYUv2 and first place on the KITTI Semantics benchmark.
Pothole detection based on disparity transformation and road surface modeling,
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DepthMatch: Semi-Supervised RGB-D Scene Parsing through Depth-Guided Regularization
A semi-supervised RGB-D scene parsing framework using patch swapping between RGB and depth, lightweight depth feature injection, and depth-derived boundary supervision reports state-of-the-art results on NYUv2 and first place on the KITTI Semantics benchmark.