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The channel-gated model is the most accurate of the authors' learned fusion arms on clean data and its gates suppress the natively biased foot-orientation channels on clean real data without test-time supervision and flag dropout bursts at 0.92-0.999 AUROC.
A multimodal capture pipeline is built that records four-view RGB-D video together with an AirPods head IMU and two Striv insole IMUs, synchronize the streams post-hoc, and generate pseudo-ground-truth with SAM 3D Body, yielding a 35-take single-subject benchmark spanning gait, turning, vertical, everyday, and clinical...
GeM-NR is proposed, a fast and flexible training-free approach for general multi-view consistent image editing, including edits that drastically change the geometry and appearance of the scene, and is demonstrated to handle edits with significant changes in geometry and appearance.
Experimental results show that this approach significantly improves 3D consistency compared to existing multi-view editing methods, and enables high-quality Gaussian splat editing with sharp details and strong fidelity to user-specified text prompts.
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