no code implementations • 27 Feb 2024 • Yazhou Xing, Yingqing He, Zeyue Tian, Xintao Wang, Qifeng Chen
Thus, instead of training the giant models from scratch, we propose to bridge the existing strong models with a shared latent representation space.
no code implementations • 2 Dec 2023 • Qiang Wen, Yazhou Xing, Zhefan Rao, Qifeng Chen
Specifically, to tailor the pre-trained latent diffusion model to operate on the RAW domain, we train a set of lightweight taming modules to inject the RAW information into the diffusion denoising process via modulating the intermediate features of UNet.
no code implementations • 29 Aug 2023 • Yazhou Xing, Amrita Mazumdar, Anjul Patney, Chao Liu, Hongxu Yin, Qifeng Chen, Jan Kautz, Iuri Frosio
We present a learning-based system to reduce these artifacts without resorting to complex acquisition mechanisms like alternating exposures or costly processing that are typical of high dynamic range (HDR) imaging.
1 code implementation • 27 Jan 2022 • Chenyang Lei, Yazhou Xing, Hao Ouyang, Qifeng Chen
A progressive propagation strategy with pseudo labels is also proposed to enhance DVP's performance on video propagation.
1 code implementation • 7 Aug 2021 • Yingqing He, Yazhou Xing, Tianjia Zhang, Qifeng Chen
Qualitative and quantitative experiments on a real-world portrait shadow dataset demonstrate that our approach achieves comparable performance with supervised shadow removal methods.
1 code implementation • CVPR 2021 • Yazhou Xing, Zian Qian, Qifeng Chen
Unprocessed RAW data is a highly valuable image format for image editing and computer vision.
2 code implementations • NeurIPS 2020 • Chenyang Lei, Yazhou Xing, Qifeng Chen
Extensive quantitative and perceptual experiments show that our approach obtains superior performance than state-of-the-art methods on blind video temporal consistency.