most citedVideo-to-Audio Generation with Hidden Alignment

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MM2025

Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning

Le Xu, Chenxing Li, Yong Ren +5

Current vision-guided audio captioning systems frequently fail to address audiovisual misalignment in real-world scenarios, such as dubbed content or off-screen sounds. To bridge t…

cs.CV2024

Improving Accuracy and Generalization for Efficient Visual Tracking

Ram Zaveri, Shivang Patel, Yu Gu +1

Efficient visual trackers overfit to their training distributions and lack generalization abilities, resulting in them performing well on their respective in-distribution (ID) test…

eess.AS2024

Video-to-Audio Generation with Fine-grained Temporal Semantics

Yuchen Hu, Yu Gu, Chenxing Li +2

With recent advances of AIGC, video generation have gained a surge of research interest in both academia and industry (e.g., Sora). However, it remains a challenge to produce tempo…

cs.SD2024

STA-V2A: Video-to-Audio Generation with Semantic and Temporal Alignment

Yong Ren, Chenxing Li, Manjie Xu +4

Visual and auditory perception are two crucial ways humans experience the world. Text-to-video generation has made remarkable progress over the past year, but the absence of harmon…

cs.SD2024★ 1 cited

Video-to-Audio Generation with Hidden Alignment

Manjie Xu, Chenxing Li, Xinyi Tu +5

Generating semantically and temporally aligned audio content in accordance with video input has become a focal point for researchers, particularly following the remarkable breakthr…

eess.IV2024

IVC: A Unified Framework for Intra- & Inter-frame Video Compression

Meiqin Liu, Chenming Xu, Yukai Gu +2

Video compression aims to reconstruct seamless frames by encoding the motion and residual information from existing frames. Previous neural video compression methods necessitate di…