Reasoning-Guided Part-Level Visual Grounding via Reinforcement Learning
Multimodal large language models (MLLMs) ground whole objects well from free-form language queries, but they struggle when the query names a part rather than the object. We trace this to a missing object-part hierarchy, since parts are localized in the same single step used for objects. We propose Object-Part Hierarchical Reflective Grounding (OP-HRG), a coarse-to-fine reasoning-guided grounding strategy that first localizes the parent object and then the part within it. A self-check then reflects on the result, with an extension to re-encode the predicted crop to inspect the region it is correcting. We introduce a part-aware GRPO framework to train our pipeline with stage-wise rewards. A...
| Authors | Kazi Sajeed Mehrab, Hani Alomari, Najibul Haque Sarker et al. |
|---|---|
| Primary category | cs.CV |
| Published | 16 July 2026 |
| Last updated at source | 16 July 2026 |
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