no code implementations • 17 Mar 2024 • Kangyang Xie, BinBin Yang, Hao Chen, Meng Wang, Cheng Zou, Hui Xue, Ming Yang, Chunhua Shen
Beyond the superiority of the text-to-image diffusion model in generating high-quality images, recent studies have attempted to uncover its potential for adapting the learned semantic knowledge to visual perception tasks.
no code implementations • 10 Mar 2024 • Guangkai Xu, Yongtao Ge, MingYu Liu, Chengxiang Fan, Kangyang Xie, Zhiyue Zhao, Hao Chen, Chunhua Shen
We show that, simply initializing image understanding models using a pre-trained UNet (or transformer) of diffusion models, it is possible to achieve remarkable transferable performance on fundamental vision perception tasks using a moderate amount of target data (even synthetic data only), including monocular depth, surface normal, image segmentation, matting, human pose estimation, among virtually many others.
1 code implementation • 30 Mar 2023 • Wen Wang, Yan Jiang, Kangyang Xie, Zide Liu, Hao Chen, Yue Cao, Xinlong Wang, Chunhua Shen
Our vid2vid-zero leverages off-the-shelf image diffusion models, and doesn't require training on any video.