SAM 3 introduces promptable concept segmentation that doubles accuracy of prior systems on images and videos while improving standard SAM segmentation performance.
Lgd: Leveraging generative descriptions for zero-shot referring image segmentation
3 Pith papers cite this work. Polarity classification is still indexing.
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A reinforced self-evolving framework (L2L) for semi-supervised referring expression segmentation that jointly optimizes the segmentation model and pseudo-labels using multimodal priors and adaptive selection.
ConTrans is a multi-scale encoder fusing convolutional inductive biases with transformer self-attention for improved local-global features in zero-shot temporal action localization.
citing papers explorer
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SAM 3: Segment Anything with Concepts
SAM 3 introduces promptable concept segmentation that doubles accuracy of prior systems on images and videos while improving standard SAM segmentation performance.
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Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
A reinforced self-evolving framework (L2L) for semi-supervised referring expression segmentation that jointly optimizes the segmentation model and pseudo-labels using multimodal priors and adaptive selection.
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ConTrans: Learning Text-enhanced Local-global Temporal Representations for Zero-shot Temporal Action Localization
ConTrans is a multi-scale encoder fusing convolutional inductive biases with transformer self-attention for improved local-global features in zero-shot temporal action localization.