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HGeo-TopoMap achieves remarkable gains in topological mapping accuracy and robustness, tackling the elusive challenge of centerline detection in autonomous driving.
Transforming point seeds into temporally consistent object instances, PS-Track sets a new benchmark in multi-object tracking without relying on traditional bounding box annotations.
HOWTransfer achieves an 86% success rate in translating human hand motions into robot actions, surpassing teleoperation in user preference.
Correcting errors in long-video understanding doesn't have to be a nightmare: IMPACT-CYCLE slashes human arbitration costs by 4.8x while boosting VQA accuracy by intelligently decomposing the task and focusing human effort where it matters most.
Autonomous vehicles can now better identify the unexpected, thanks to a new method that boosts out-of-distribution detection by up to 20% without retraining.
Achieve state-of-the-art panoramic segmentation by training on local perspective views and generalizing to full 360掳 images, even with geometric distortions and unseen classes.
