4 papers
SEDiT: Mask-Free Video Subtitle Erasure via One-step Diffusion Transformer
Zheng Hui, Yunlong Bai
Recent breakthroughs in video diffusion models have significantly accelerated the development of video editing techniques. However, existing methods often rely on inpainting video…
EraserDiT: Fast Video Inpainting with Diffusion Transformer Model
Jie Liu, Zheng Hui
Video object removal and inpainting are critical tasks in the fields of computer vision and multimedia processing, aimed at restoring missing or corrupted regions in video sequence…
VideoElevator: Elevating Video Generation Quality with Versatile Text-to-Image Diffusion Models
Yabo Zhang, Yuxiang Wei, Xianhui Lin +5
Text-to-image diffusion models (T2I) have demonstrated unprecedented capabilities in creating realistic and aesthetic images. On the contrary, text-to-video diffusion models (T2V)…
DreaMoving: A Human Video Generation Framework based on Diffusion Models
Mengyang Feng, Jinlin Liu, Kai Yu +13
In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity…