Learned 2D data association and uncertainty—not recurrent architectures—drive the performance gains of deep visual SLAM, as shown by integrating them into classical ORB-SLAM3.
Deep patch vi- sual odometry.ArXiv, abs/2208.04726
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abstract
We propose Deep Patch Visual Odometry (DPVO), a new deep learning system for monocular Visual Odometry (VO). DPVO uses a novel recurrent network architecture designed for tracking image patches across time. Recent approaches to VO have significantly improved the state-of-the-art accuracy by using deep networks to predict dense flow between video frames. However, using dense flow incurs a large computational cost, making these previous methods impractical for many use cases. Despite this, it has been assumed that dense flow is important as it provides additional redundancy against incorrect matches. DPVO disproves this assumption, showing that it is possible to get the best accuracy and efficiency by exploiting the advantages of sparse patch-based matching over dense flow. DPVO introduces a novel recurrent update operator for patch based correspondence coupled with differentiable bundle adjustment. On Standard benchmarks, DPVO outperforms all prior work, including the learning-based state-of-the-art VO-system (DROID) using a third of the memory while running 3x faster on average. Code is available at https://github.com/princeton-vl/DPVO
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cs.CV 2years
2026 2representative citing papers
Video-based 3D mesh recovery extracts gait parameters that correlate with sensor measurements and are associated with higher fall risk in older adults.
citing papers explorer
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Why does Deep Learning Improve Visual SLAM?
Learned 2D data association and uncertainty—not recurrent architectures—drive the performance gains of deep visual SLAM, as shown by integrating them into classical ORB-SLAM3.
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Fall Risk and Gait Analysis in Community-Dwelling Older Adults using World-Spaced 3D Human Mesh Recovery
Video-based 3D mesh recovery extracts gait parameters that correlate with sensor measurements and are associated with higher fall risk in older adults.