most citedWeb Video Categorization based on Wikipedia Categories and Content-Duplicated Open Resources

4 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Break-for-Make: Modular Low-Rank Adaptations for Composable Content-Style Customization

Yu Xu, Fan Tang, Juan Cao +5

Personalized generation paradigms empower designers to customize visual intellectual properties with the help of textual descriptions by tuning or adapting pre-trained text-to-imag…

cs.CV20241 cited

U-VAP: User-specified Visual Appearance Personalization via Decoupled Self Augmentation

You Wu, Kean Liu, Xiaoyue Mi +3

Concept personalization methods enable large text-to-image models to learn specific subjects (e.g., objects/poses/3D models) and synthesize renditions in new contexts. Given that t…

cs.CV2024

Make-Your-Anchor: A Diffusion-based 2D Avatar Generation Framework

Ziyao Huang, Fan Tang, Yong Zhang +4

Despite the remarkable process of talking-head-based avatar-creating solutions, directly generating anchor-style videos with full-body motions remains challenging. In this study, w…

cs.MM20104 cited

Web Video Categorization based on Wikipedia Categories and Content-Duplicated Open Resources

Zhineng Chen, Juan Cao, Yicheng Song +2

This paper presents a novel approach for web video categorization by leveraging Wikipedia categories (WikiCs) and open resources describing the same content as the video, i.e., con…

cs.MM2010

Context-Oriented Web Video Tag Recommendation

Zhineng Chen, Juan Cao, Yicheng Song +3

Tag recommendation is a common way to enrich the textual annotation of multimedia contents. However, state-of-the-art recommendation methods are built upon the pair-wised tag relev…