5 papers
Lost in the Hype: Revealing and Dissecting the Performance Degradation of Medical Multimodal Large Language Models in Image Classification
Xun Zhu, Fanbin Mo, Xi Chen +6
The rise of multimodal large language models (MLLMs) has sparked an unprecedented wave of applications in the field of medical imaging analysis. However, as one of the earliest and…
MedM-VL: What Makes a Good Medical LVLM?
Yiming Shi, Shaoshuai Yang, Xun Zhu +4
Medical image analysis is essential in modern healthcare. Deep learning has redirected research focus toward complex medical multimodal tasks, including report generation and visua…
InfiniteTalk: Audio-driven Video Generation for Sparse-Frame Video Dubbing
Shaoshu Yang, Zhe Kong, Feng Gao +8
Recent breakthroughs in video AIGC have ushered in a transformative era for audio-driven human animation. However, conventional video dubbing techniques remain constrained to mouth…
DAM-VSR: Disentanglement of Appearance and Motion for Video Super-Resolution
Zhe Kong, Le Li, Yong Zhang +8
Real-world video super-resolution (VSR) presents significant challenges due to complex and unpredictable degradations. Although some recent methods utilize image diffusion models f…
CV-VAE: A Compatible Video VAE for Latent Generative Video Models
Sijie Zhao, Yong Zhang, Xiaodong Cun +5
Spatio-temporal compression of videos, utilizing networks such as Variational Autoencoders (VAE), plays a crucial role in OpenAI's SORA and numerous other video generative models.…