DINO-VO achieves state-of-the-art monocular visual odometry accuracy and generalization by training a differentiable patch selector together with multi-task features and inverse-depth bundle adjustment.
Deepfactors: Real-time probabilistic dense monocular slam.IEEE Robotics and Automation Letters, 5 (2):721–728
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Flow4DGS-SLAM uses optical flow to generate motion masks, initialize poses, and guide 4D Gaussian modeling with scene flow and GMM for temporal properties, claiming SOTA results in dynamic tracking and reconstruction.
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DINO-VO: Learning Where to Focus for Enhanced State Estimation
DINO-VO achieves state-of-the-art monocular visual odometry accuracy and generalization by training a differentiable patch selector together with multi-task features and inverse-depth bundle adjustment.
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Flow4DGS-SLAM: Optical Flow-Guided 4D Gaussian Splatting SLAM
Flow4DGS-SLAM uses optical flow to generate motion masks, initialize poses, and guide 4D Gaussian modeling with scene flow and GMM for temporal properties, claiming SOTA results in dynamic tracking and reconstruction.