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cs.CV2026

Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs

Zeyi Huang, Yuyang Ji, Xiaofang Wang +11

Long-form video understanding with Large Vision Language Models is challenged by the need to analyze temporally dispersed yet spatially concentrated key moments within limited cont…

cs.CV2024

Apollo: An Exploration of Video Understanding in Large Multimodal Models

Orr Zohar, Xiaohan Wang, Yann Dubois +9

Despite the rapid integration of video perception capabilities into Large Multimodal Models (LMMs), the underlying mechanisms driving their video understanding remain poorly unders…

cs.CV2024

Accelerating Multimodal Large Language Models by Searching Optimal Vision Token Reduction

Shiyu Zhao, Zhenting Wang, Felix Juefei-Xu +7

Prevailing Multimodal Large Language Models (MLLMs) encode the input image(s) as vision tokens and feed them into the language backbone, similar to how Large Language Models (LLMs)…

cs.CV2024

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation

Bolin Lai, Felix Juefei-Xu, Miao Liu +8

Text-guided image manipulation has experienced notable advancement in recent years. In order to mitigate linguistic ambiguity, few-shot learning with visual examples has been appli…

cs.CV2024

Imagine yourself: Tuning-Free Personalized Image Generation

Zecheng He, Bo Sun, Felix Juefei-Xu +14

Diffusion models have demonstrated remarkable efficacy across various image-to-image tasks. In this research, we introduce Imagine yourself, a state-of-the-art model designed for p…