12 citations · 21 across the 6 of their papers we have counts for
6 papers
OmniVAE: An Audio-Video VAE with Cross-Modal Alignment for Joint Generation
Jun Zhan, Chen Yang, Yitian Gong +23
Recent generative models are moving beyond silent video or standalone audio synthesis toward the joint generation of synchronized audio and video. Despite this progress, jointly ge…
MOVA: Towards Scalable and Synchronized Video-Audio Generation
OpenMOSS Team, Donghua Yu, Mingshu Chen +38
Audio is indispensable for real-world video, yet generation models have largely overlooked audio components. Current approaches to producing audio-visual content often rely on casc…
Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k
Zangwei Zheng, Xiangyu Peng, Yuxuan Lou +30
Video generation models have achieved remarkable progress in the past year. The quality of AI video continues to improve, but at the cost of larger model size, increased data quant…
Open-Sora: Democratizing Efficient Video Production for All
Zangwei Zheng, Xiangyu Peng, Tianji Yang +6
Vision and language are the two foundational senses for humans, and they build up our cognitive ability and intelligence. While significant breakthroughs have been made in AI langu…
More Than Positive and Negative: Communicating Fine Granularity in Medical Diagnosis
Xiangyu Peng, Kai Wang, Jianfei Yang +2
With the advance of deep learning, much progress has been made in building powerful artificial intelligence (AI) systems for automatic Chest X-ray (CXR) analysis. Most existing AI…
CAFE: Learning to Condense Dataset by Aligning Features
Kai Wang, Bo Zhao, Xiangyu Peng +7
Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one. State-of-the-art approaches largely rel…