ConceptSeg-R1 uses Meta-GRPO meta-RL to learn transferable rules from visual demonstrations and apply them via concept translation for generalized concept segmentation across CI, CD, and CR levels.
Lisa: Reasoning segmentation via large language model
2 Pith papers cite this work. Polarity classification is still indexing.
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X2SAM unifies any-segmentation across images and videos in one MLLM by adding a Mask Memory module for temporal consistency and joint training on mixed datasets.
citing papers explorer
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ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning
ConceptSeg-R1 uses Meta-GRPO meta-RL to learn transferable rules from visual demonstrations and apply them via concept translation for generalized concept segmentation across CI, CD, and CR levels.
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X2SAM: Any Segmentation in Images and Videos
X2SAM unifies any-segmentation across images and videos in one MLLM by adding a Mask Memory module for temporal consistency and joint training on mixed datasets.