7 papers
AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation
Zeyue Tian, Lei Ke, Zhaoyang Liu +8
Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a unified multimodal modeling framework,…
Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing
Zeyue Tian, Binxin Yang, Zhaoyang Liu +8
Recent progress in multimodal models has spurred rapid advances in audio understanding, generation, and editing. However, these capabilities are typically addressed by specialized…
AudioX: A Unified Framework for Anything-to-Audio Generation
Zeyue Tian, Zhaoyang Liu, Yizhu Jin +6
Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a unified multimodal modeling framework,…
VAInpaint: Zero-Shot Video-Audio inpainting framework with LLMs-driven Module
Kam Man Wu, Zeyue Tian, Liya Ji +1
Video and audio inpainting for mixed audio-visual content has become a crucial task in multimedia editing recently. However, precisely removing an object and its corresponding audi…
ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data
Zhaoyang Liu, Jingjing Xie, Zichen Ding +27
Vision-Language Models (VLMs) have enabled computer use agents (CUAs) that operate GUIs autonomously, showing great potential, yet progress is limited by the lack of large-scale, o…
VidMuse: A Simple Video-to-Music Generation Framework with Long-Short-Term Modeling
Zeyue Tian, Zhaoyang Liu, Ruibin Yuan +6
In this work, we systematically study music generation conditioned solely on the video. First, we present a large-scale dataset comprising 360K video-music pairs, including various…