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GRAIL achieves an impressive 84% success rate in real-world object pick-up tasks using only synthetic data, revolutionizing humanoid robot training.
Stop wrestling with incompatible human body models: SOMA lets you mix and match SMPL, SMPL-X, and more, unlocking the power of diverse datasets in a single, differentiable pipeline.
Forget SLAM, ReCoSplat uses a "Render-and-Compare" module to autoregressively refine Gaussian Splatting reconstructions, even from unposed video, achieving SOTA novel view synthesis.
LVLMs already highlight the right image regions, you just need to amplify their "Positive Attention Dynamics" to cut through the noise and reduce hallucinations.
