Motion-aware contrastive learning on mask tubes improves temporal panoptic scene graph generation over pooling-based methods on video and 4D datasets.
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Attention-Mamba uses parallel branches, Recursive Alignment Module, and Mamba-enhanced attention to report highest segmentation accuracy on Synapse, ACDC, ISIC-2018, and PH2 with 14.05M parameters and 8.94 GFLOPs.
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Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation
Motion-aware contrastive learning on mask tubes improves temporal panoptic scene graph generation over pooling-based methods on video and 4D datasets.
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Attention-Mamba: A Mamba-Enhanced Multi-Scale Parallel Inference Network for Medical Image Segmentation
Attention-Mamba uses parallel branches, Recursive Alignment Module, and Mamba-enhanced attention to report highest segmentation accuracy on Synapse, ACDC, ISIC-2018, and PH2 with 14.05M parameters and 8.94 GFLOPs.