@ModelScope2022: AMAP CV Lab introduces ABot-Recon, turning long video streams into camera paths and 3D point clouds in real time. https…

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Summary

AMAP CV Lab has introduced ABot-Recon, a real-time AI system that processes long video streams to generate 3D point clouds and camera paths, featuring stable performance and open-source code released under Apache 2.0.

AMAP CV Lab introduces ABot-Recon, turning long video streams into camera paths and 3D point clouds in real time. https://modelscope.ai/models/amap_cvlab/ABot-Recon… 4.35 m ATE and 91.81% F1 on Oxford Spires, without loop closure. 24.45 FPS with only 6.71 GiB memory in the official test. Looks at just the latest 12 frames, so speed and memory stay stable even as videos get longer. Supports streams up to 22,000 frames and builds them into one continuous 3D reconstruction. Checkpoint, inference, and evaluation code released. Code: Apache 2.0; weights use separate model terms.
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AMAP CV Lab introduces ABot-Recon, turning long video streams into camera paths and 3D point clouds in real time. https://modelscope.ai/models/amap_cvlab/ABot-Recon…

4.35 m ATE and 91.81% F1 on Oxford Spires, without loop closure. 24.45 FPS with only 6.71 GiB memory in the official test. Looks at just the latest 12 frames, so speed and memory stay stable even as videos get longer. Supports streams up to 22,000 frames and builds them into one continuous 3D reconstruction. Checkpoint, inference, and evaluation code released. Code: Apache 2.0; weights use separate model terms.

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