AV1 motion vectors filtered by cosine consistency yield dense sub-pixel correspondences that support structure-from-motion on short video clips with lower CPU cost and higher match density than sequential SIFT.
Are we ready for autonomous driving? the kitti vision benchmark suite
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
OCD SLAM adds cross-disparity inconsistency checks and object-level motion classification to ORB-SLAM2, reporting better trajectory accuracy than prior dynamic SLAM methods on KITTI sequences.
citing papers explorer
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Leveraging AV1 motion vectors for Fast and Dense Feature Matching
AV1 motion vectors filtered by cosine consistency yield dense sub-pixel correspondences that support structure-from-motion on short video clips with lower CPU cost and higher match density than sequential SIFT.
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A Stereo Visual SLAM System Using Object-Level Motion Estimation and Geometric Filtering Based on Cross Disparity
OCD SLAM adds cross-disparity inconsistency checks and object-level motion classification to ORB-SLAM2, reporting better trajectory accuracy than prior dynamic SLAM methods on KITTI sequences.