COCOTree is a 21K-image benchmark with 1.8M nodes and an OTQ metric for the new task of open tree-structured visual decomposition.
SAM4MLLM: Enhance multi-modal large language model for referring expression segmenta- tion
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
VASA is a vision-guided agent for open ad-hoc segmentation that creates and validates masks through planning, tool use, and error recovery, outperforming baselines on the new PARS benchmark and RefCOCOm.
Tarot-SAM3 delivers a training-free pipeline for segmenting images from arbitrary referring expressions via expression reasoning prompts and DINOv3-based mask self-refinement.
citing papers explorer
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COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition
COCOTree is a 21K-image benchmark with 1.8M nodes and an OTQ metric for the new task of open tree-structured visual decomposition.
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Vision Harnessing Agent for Open Ad-hoc Segmentation
VASA is a vision-guided agent for open ad-hoc segmentation that creates and validates masks through planning, tool use, and error recovery, outperforming baselines on the new PARS benchmark and RefCOCOm.
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Tarot-SAM3: Training-free SAM3 for Any Referring Expression Segmentation
Tarot-SAM3 delivers a training-free pipeline for segmenting images from arbitrary referring expressions via expression reasoning prompts and DINOv3-based mask self-refinement.