MLG-Stereo adds multi-granularity feature extraction, local-global cost volumes, and guided recurrent refinement to ViT stereo matching, yielding competitive results on Middlebury, KITTI-2015, and strong results on KITTI-2012.
Foundationstereo: Zero-shot stereo matching
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A JAX-implemented flow-based equivariant model for multi-embodiment grasping that deduces kinematics from geometry to support variable-DoF grippers with a new dataset of 25k scenes and 20M grasps.
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MLG-Stereo: ViT Based Stereo Matching with Multi-Stage Local-Global Enhancement
MLG-Stereo adds multi-granularity feature extraction, local-global cost volumes, and guided recurrent refinement to ViT stereo matching, yielding competitive results on Middlebury, KITTI-2015, and strong results on KITTI-2012.
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Towards a Multi-Embodied Grasping Agent
A JAX-implemented flow-based equivariant model for multi-embodiment grasping that deduces kinematics from geometry to support variable-DoF grippers with a new dataset of 25k scenes and 20M grasps.