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.
Tartanair: A dataset to push the limits of visual slam
3 Pith papers cite this work. Polarity classification is still indexing.
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MoGe-2 recovers metric-scale 3D point maps with fine details from single images via data refinement and extension of affine-invariant predictions.
HY-World 2.0 generates and reconstructs high-fidelity navigable 3D Gaussian Splatting worlds from text, images, or videos via upgraded panorama, planning, expansion, and composition modules, with released code claiming open-source SOTA performance.
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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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MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details
MoGe-2 recovers metric-scale 3D point maps with fine details from single images via data refinement and extension of affine-invariant predictions.
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HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds
HY-World 2.0 generates and reconstructs high-fidelity navigable 3D Gaussian Splatting worlds from text, images, or videos via upgraded panorama, planning, expansion, and composition modules, with released code claiming open-source SOTA performance.