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This work proposes VOP-Nav, a novel navigation system that combines the geometric safety of VO with the agile adaptability of end-to-end learning and validates the system's robustness and efficiency in complex indoor and outdoor dynamic environments.
KLTNet is proposed, a lightweight learning-based, plug-and-play sparse feature tracker designed to replace classical KLT trackers in KLT-based VIO front ends and predicts anisotropic confidence weights supervised through differentiable multi-view triangulation, which can be used as observation weights in compatible VIO...
An efficient generative framework designed to improve in-the-wild robustness under diverse real capture conditions and demonstrate strong perceptual quality, semantic fidelity, and temporal consistency on unseen videos, as well as improved robustness in downstream 3D reconstruction under severe motion blur.
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