3 papers
cs.CV2025
Seeing through Imagination: Learning Scene Geometry via Implicit Spatial World Modeling
Meng Cao, Haokun Lin, Haoyuan Li +6
Spatial reasoning, the ability to understand and interpret the 3D structure of the world, is a critical yet underdeveloped capability in Multimodal Large Language Models (MLLMs). C…
cs.RO2025
Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision
Xiaofeng Han, Shunpeng Chen, Zenghuang Fu +9
Robot vision has greatly benefited from advancements in multimodal fusion techniques and vision-language models (VLMs). We adopt a task-oriented perspective to systematically revie…
cs.CV2025
3D-MoRe: Unified Modal-Contextual Reasoning for Embodied Question Answering
Rongtao Xu, Han Gao, Mingming Yu +6
With the growing need for diverse and scalable data in indoor scene tasks, such as question answering and dense captioning, we propose 3D-MoRe, a novel paradigm designed to generat…