With the burgeoning growth of online video platforms and the escalating volume of video
content, the demand for proficient video understanding tools has intensified markedly. Given …

A well-known dilemma in large vision-language models (eg, GPT-4, LLaVA) is that while
increasing the number of vision tokens generally enhances visual understanding, it also …

Abstract We introduce Diff-Tracker, a novel approach for the challenging unsupervised
visual tracking task leveraging the pre-trained text-to-image diffusion model. Our main idea …

Narrative videos, such as movies, pose significant challenges in video understanding due to
their rich contexts (characters, dialogues, storylines) and diverse demands (identify who …

Recent advancements in large-scale video-language models have shown significant
potential for real-time planning and detailed interactions. However, their high computational …

Large language models (LLMs) have revolutionized video-based computer vision
applications, including action recognition, anomaly detection, and video summarization …

We introduce Vinci, a real-time embodied smart assistant built upon an egocentric vision-
language model. Designed for deployment on portable devices such as smartphones and …

The advent of real-time large multimodal models (LMMs) like GPT-4o has sparked
considerable interest in efficient LMMs. LMM frameworks typically encode visual inputs into …

This paper presents StreamChat, a novel approach that enhances the interaction
capabilities of Large Multimodal Models (LMMs) with streaming video content. In streaming …

The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes
the refereed proceedings of the 18th European Conference on Computer Vision, ECCV …