Dense Reward for Multi-View 3D Reasoning with Global Maps and Local Views
DR-MV3D presents a map-grounded learning framework with dense rewards to improve multi-view 3D visual question answering through global map construction, view-trajectory planning,…
Hugging Face · Daily Papers
·Jiho Choi, Seonho Lee
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·▲ 4 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Jiho Choi, Seonho Lee, Seojeong Park, Hyunjung Shim
- 4 upvotes da comunidade
- Temas: MV3D-VQA, multimodal LLMs, sparse supervision, cross-view reasoning, view selection, dense reward
Resumo
Resumo original (em inglês), extraído do paper:
DR-MV3D presents a map-grounded learning framework with dense rewards to improve multi-view 3D visual question answering through global map construction, view-trajectory planning, and egocentric grounding.
