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Research questionHow can visual tool pipelines adapt when dense, occluded scenes or domain shift defeat fixed orchestration?Fixed pipelines can fail when scene conditions change, because a tool sequence or parameter setting that works on ordinary images may miss small or occluded objects or generalize poorly across domains. These failures are especially consequential when the task requires combining detection, segmentation, and post-processing operations.
AI
Code Generation & Program Synthesis
Computer Vision
Image & Video Processing
Machine Learning
Latest papersRecent research connected to this question, newest first.VTOS: Learning to Orchestrate Vision Tools by Co-Searching Solutions and ObserversThe evidence concerns executable compositions of open-vocabulary detection, segmentation, and post-processing tools for dense object counting on LVIS-Count and zero-shot plant-disease segmentation on PlantSeg-OOD. The reported settings include threshold calibration, non-maximum suppression, image slicing, mask refinement, and domain generalization; broader tasks and deployment constraints are not established.research paper · Sep 2, 2026
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