Self-supervised fine-tuning of SuperPoint using visual odometry reprojection errors as labels produces more uniform features and improves trajectory estimates on the Pohang dataset, according to qualitative results only.
Moving on to dynamic environ- ments: Visual odometry using feature classification,
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Good Deep Features to Track: Self-Supervised Feature Extraction and Tracking in Visual Odometry
Self-supervised fine-tuning of SuperPoint using visual odometry reprojection errors as labels produces more uniform features and improves trajectory estimates on the Pohang dataset, according to qualitative results only.