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20242026
most citedVideo Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding

19 citations · 35 across the 13 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024

Vinci: A Real-time Embodied Smart Assistant based on Egocentric Vision-Language Model

Yifei Huang, Jilan Xu, Baoqi Pei +15

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 wearabl…

cs.CV2024

CG-Bench: Clue-grounded Question Answering Benchmark for Long Video Understanding

Guo Chen, Yicheng Liu, Yifei Huang +6

Most existing video understanding benchmarks for multimodal large language models (MLLMs) focus only on short videos. The limited number of benchmarks for long video understanding…

cs.CV2024

EgoVideo: Exploring Egocentric Foundation Model and Downstream Adaptation

Baoqi Pei, Guo Chen, Jilan Xu +8

In this report, we present our solutions to the EgoVis Challenges in CVPR 2024, including five tracks in the Ego4D challenge and three tracks in the EPIC-Kitchens challenge. Buildi…

cs.CV2024★ 19 cited

Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding

Guo Chen, Yifei Huang, Jilan Xu +7

Understanding videos is one of the fundamental directions in computer vision research, with extensive efforts dedicated to exploring various architectures such as RNN, 3D CNN, and…

cs.CV2024

EgoExoLearn: A Dataset for Bridging Asynchronous Ego- and Exo-centric View of Procedural Activities in Real World

Yifei Huang, Guo Chen, Jilan Xu +8

Being able to map the activities of others into one's own point of view is one fundamental human skill even from a very early age. Taking a step toward understanding this human abi…

cs.CV2024★ 16 cited

InternVideo2: Scaling Foundation Models for Multimodal Video Understanding

Yi Wang, Kunchang Li, Xinhao Li +17

We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the state-of-the-art results in video recognition, video-text tasks, and video-centric dialog…