no code implementations • 26 May 2024 • Jinlin Liu, Kai Yu, Mengyang Feng, Xiefan Guo, Miaomiao Cui
Training on real-world videos enhanced with this innovative motion depiction approach, our model generates videos exhibiting coherent movement in both foreground subjects and their surrounding contexts.
1 code implementation • 6 Apr 2024 • Xiefan Guo, Jinlin Liu, Miaomiao Cui, Jiankai Li, Hongyu Yang, Di Huang
Recent strides in the development of diffusion models, exemplified by advancements such as Stable Diffusion, have underscored their remarkable prowess in generating visually compelling images.
no code implementations • 8 Dec 2023 • Mengyang Feng, Jinlin Liu, Kai Yu, Yuan YAO, Zheng Hui, Xiefan Guo, Xianhui Lin, Haolan Xue, Chen Shi, Xiaowen Li, Aojie Li, Xiaoyang Kang, Biwen Lei, Miaomiao Cui, Peiran Ren, Xuansong Xie
In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos.
1 code implementation • 22 Nov 2023 • Mengyang Feng, Jinlin Liu, Miaomiao Cui, Xuansong Xie
This is a technical report on the 360-degree panoramic image generation task based on diffusion models.
no code implementations • 22 Nov 2023 • Kai Yu, Jinlin Liu, Mengyang Feng, Miaomiao Cui, Xuansong Xie
After the progressive training, the LoRA learns the 3D information of the generated object and eventually turns to an object-level 3D prior.
no code implementations • 10 Mar 2022 • Jinlin Liu
We use dynamic background video instead of static background for accurate matting.
1 code implementation • CVPR 2020 • Jinlin Liu, Yuan YAO, Wendi Hou, Miaomiao Cui, Xuansong Xie, Chang-Shui Zhang, Xian-Sheng Hua
In this paper, we propose to use coarse annotated data coupled with fine annotated data to boost end-to-end semantic human matting without trimaps as extra input.
Ranked #9 on Image Matting on AM-2K
no code implementations • 9 Sep 2019 • Jinlin Liu, Yuan YAO, Jianqiang Ren
The proposed acceleration framework makes it possible to generate high resolution images using less training time with limited hardware resource.
no code implementations • 19 Aug 2019 • Jiahui Qiu, Yangming Zhou, Zhiyuan Ma, Tong Ruan, Jinlin Liu, Jing Sun
Clinical text structuring is a critical and fundamental task for clinical research.