3 papers
cs.CV2025
N3D-VLM: Native 3D Grounding Enables Accurate Spatial Reasoning in Vision-Language Models
Yuxin Wang, Lei Ke, Boqiang Zhang +6
While current multimodal models can answer questions based on 2D images, they lack intrinsic 3D object perception, limiting their ability to comprehend spatial relationships and de…
cs.CV2025
StreamingAssistant: Efficient Visual Token Pruning for Accelerating Online Video Understanding
Xinqi Jin, Hanxun Yu, Bohan Yu +8
Online video understanding is essential for applications like public surveillance and AI glasses. However, applying Multimodal Large Language Models (MLLMs) to this domain is chall…
cs.CV2025
Inst3D-LMM: Instance-Aware 3D Scene Understanding with Multi-modal Instruction Tuning
Hanxun Yu, Wentong Li, Song Wang +2
Despite encouraging progress in 3D scene understanding, it remains challenging to develop an effective Large Multi-modal Model (LMM) that is capable of understanding and reasoning…