GESS introduces joint semantic-normal and depth stability prediction heads, the SDAK keypoint mechanism, and the UTCF descriptor fusion module to leverage multi-cue synergy for improved robustness and discriminability.
Xfeat: Accelerated features for lightweight image matching
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
EpiDiffVO uses sparse epipolar matching, diffusion-based refinement, and graph neural network subset selection to reduce correspondence redundancy while maintaining robust relative pose estimation on TartanAir and KITTI datasets.
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GESS: Multi-cue Guided Local Feature Learning via Geometric and Semantic Synergy
GESS introduces joint semantic-normal and depth stability prediction heads, the SDAK keypoint mechanism, and the UTCF descriptor fusion module to leverage multi-cue synergy for improved robustness and discriminability.
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EpiDiffVO: Geometry-Aware Epipolar Diffusion for Robust Visual Odometry
EpiDiffVO uses sparse epipolar matching, diffusion-based refinement, and graph neural network subset selection to reduce correspondence redundancy while maintaining robust relative pose estimation on TartanAir and KITTI datasets.