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Found 4 papers, 1 papers with code
DK-SLAM: Monocular Visual SLAM with Deep Keypoints Adaptive Learning, Tracking and Loop-Closing
Unreliable feature extraction and matching in handcrafted features undermine the performance of visual SLAM in complex real-world scenarios.
Distributed bundle adjustment with block-based sparse matrix compression for super large scale datasets
Different from them, we utilize the exact LM algorithm to conduct global bundle adjustment where the formation of the reduced camera system (RCS) is actually parallelized and executed in a distributed way.
SelfOdom: Self-supervised Egomotion and Depth Learning via Bi-directional Coarse-to-Fine Scale Recovery
To address this, we propose SelfOdom, a self-supervised dual-network framework that can robustly and consistently learn and generate pose and depth estimates in global scale from monocular images.
Subspace Clustering for Panel Data with Interactive Effects
The factor loadings are assumed to be in different subspaces and the subspace clustering for factor loadings are considered.
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