Autoregressive probabilistic world models trained on raw videos yield emergent object segmentation, 3D controllability, and physical relationship inference via multi-future motion correlation analysis.
Segment any- thing is not always perfect: An investigation of sam on dif- ferent real-world applications
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Stabilized SegFormer-B5 reaches 0.4572 mIoU SOTA on original Apple DMS split; 80/10/10 split reaches 0.5276 mIoU but degrades real-world OOD performance per qualitative review.
citing papers explorer
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Physical Object Understanding with a Physically Controllable World Model
Autoregressive probabilistic world models trained on raw videos yield emergent object segmentation, 3D controllability, and physical relationship inference via multi-future motion correlation analysis.
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Revitalizing Dense Material Segmentation: Stabilized Vision Transformers and the Generalization Paradox
Stabilized SegFormer-B5 reaches 0.4572 mIoU SOTA on original Apple DMS split; 80/10/10 split reaches 0.5276 mIoU but degrades real-world OOD performance per qualitative review.