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Main Authors: Wang, Zhiting, Zhou, Qiangong, Yang, Kangjie, Liu, Zongyang, Mao, Xin
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.07325
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author Wang, Zhiting
Zhou, Qiangong
Yang, Kangjie
Liu, Zongyang
Mao, Xin
author_facet Wang, Zhiting
Zhou, Qiangong
Yang, Kangjie
Liu, Zongyang
Mao, Xin
contents This technical report presents the implementation of a state-of-the-art video encoder for video-text modal alignment and a video conversation framework called HiLight, which features dual visual towers. The work is divided into two main parts: 1.alignment of video and text modalities; 2.convenient and efficient way to interact with users. Our goal is to address the task of video comprehension in the context of billiards. The report includes a discussion of the concepts and the final solution developed during the task's implementation.
format Preprint
id arxiv_https___arxiv_org_abs_2407_07325
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle HiLight: Technical Report on the Motern AI Video Language Model
Wang, Zhiting
Zhou, Qiangong
Yang, Kangjie
Liu, Zongyang
Mao, Xin
Computer Vision and Pattern Recognition
Computation and Language
Multimedia
Image and Video Processing
This technical report presents the implementation of a state-of-the-art video encoder for video-text modal alignment and a video conversation framework called HiLight, which features dual visual towers. The work is divided into two main parts: 1.alignment of video and text modalities; 2.convenient and efficient way to interact with users. Our goal is to address the task of video comprehension in the context of billiards. The report includes a discussion of the concepts and the final solution developed during the task's implementation.
title HiLight: Technical Report on the Motern AI Video Language Model
topic Computer Vision and Pattern Recognition
Computation and Language
Multimedia
Image and Video Processing
url https://arxiv.org/abs/2407.07325