9 papers
FATE: Frame-Level Audio-Visual Temporal Embedding
Kaisi Guan, Bingzi Zhang, Xihua Wang +4
When a dog opens its mouth and barks, humans naturally recognize what the sound is and when it occurs. Building audio-visual models with this same ability requires representations…
Taming Text-to-Sounding Video Generation via Advanced Modality Condition and Interaction
Kaisi Guan, Xihua Wang, Zhengfeng Lai +5
This study focuses on a challenging yet promising task, Text-to-Sounding-Video (T2SV) generation, which aims to generate a video with synchronized audio from text conditions, meanw…
AVOC: Enhancing Hour-Level Audio-Video Understanding in Omni-Modal LLMs via Retrieval-Inspired Token Compression
Yijing Chen, Wenhui Tan, Xiaoyi Yu +7
Multimodal Large Language Models have achieved remarkable progress in short-form audio-video understanding, yet long-form audio-video comprehension remains challenged by limited co…
SyncDPO: Enhancing Temporal Synchronization in Video-Audio Joint Generation via Preference Learning
Xin Cheng, Xihua Wang, Ying Ba +5
Recent advancements in video-audio joint generation have achieved remarkable success in semantic correspondence. However, achieving precise temporal synchronization, which requires…
HuM-Eval: A Coarse-to-Fine Framework for Human-Centric Video Evaluation
Bingzi Zhang, Kaisi Guan, Ruihua Song
Video generation models have developed rapidly in recent years, where generating natural human motion plays a pivotal role. However, accurately evaluating the quality of generated…
VSSFlow: Unifying Video-conditioned Sound and Speech Generation via Joint Learning
Xin Cheng, Yuyue Wang, Xihua Wang +7
Video-conditioned audio generation, including Video-to-Sound (V2S) and Visual Text-to-Speech (VisualTTS), has traditionally been treated as distinct tasks, leaving the potential fo…