PoseFM is the first method to reformulate monocular frame-to-frame visual odometry as a flow-matching generative model that predicts camera pose distributions for built-in uncertainty.
Direct sparse odometry.IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(3):611–625
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The survey reviews spatial memory methods across 88 references, defines α as peak runtime memory over map size, profiles neural methods showing α from 2.3 to 215 on A100 GPU, and proposes a standardized evaluation protocol plus α-aware budgeting.
citing papers explorer
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PoseFM: Relative Camera Pose Estimation Through Flow Matching
PoseFM is the first method to reformulate monocular frame-to-frame visual odometry as a flow-matching generative model that predicts camera pose distributions for built-in uncertainty.
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A Survey of Spatial Memory Representations for Efficient Robot Navigation
The survey reviews spatial memory methods across 88 references, defines α as peak runtime memory over map size, profiles neural methods showing α from 2.3 to 215 on A100 GPU, and proposes a standardized evaluation protocol plus α-aware budgeting.