27 citations · 71 across the 26 of their papers we have counts for
6 papers · 1 filter
CADER: Confidence-Aware Dynamic Evidence Reasoning for Long-Video Understanding
Jinlong Yang, Wenhao Zhang, Kuanwei Lin +1
Long-video understanding increasingly relies on large vision-language models and tool-augmented reasoning, but most systems apply the same inference procedure to every example rega…
VideoMem: Enhancing Ultra-Long Video Understanding via Adaptive Memory Management
Hongbo Jin, Qingyuan Wang, Wenhao Zhang +2
Ultra long video understanding remains an open challenge, as existing vision language models (VLMs) falter on such content due to limited context length and inefficient long term m…
Building Egocentric Procedural AI Assistant: Methods, Benchmarks, and Challenges
Junlong Li, Huaiyuan Xu, Sijie Cheng +4
Driven by recent advances in vision-language models (VLMs) and egocentric perception research, the emerging topic of an egocentric procedural AI assistant (EgoProceAssist) is intro…
VidEgoThink: Assessing Egocentric Video Understanding Capabilities for Embodied AI
Sijie Cheng, Kechen Fang, Yangyang Yu +6
Recent advancements in Multi-modal Large Language Models (MLLMs) have opened new avenues for applications in Embodied AI. Building on previous work, EgoThink, we introduce VidEgoTh…
ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal Models
Chunjiang Ge, Sijie Cheng, Ziming Wang +6
High-resolution Large Multimodal Models (LMMs) encounter the challenges of excessive visual tokens and quadratic visual complexity. Current high-resolution LMMs address the quadrat…
EgoThink: Evaluating First-Person Perspective Thinking Capability of Vision-Language Models
Sijie Cheng, Zhicheng Guo, Jingwen Wu +4
Vision-language models (VLMs) have recently shown promising results in traditional downstream tasks. Evaluation studies have emerged to assess their abilities, with the majority fo…