no code implementations • 1 Apr 2024 • Hu Yu, Hao Luo, Fan Wang, Feng Zhao
The correspondence between input text and the generated image exhibits opacity, wherein minor textual modifications can induce substantial deviations in the generated image.
no code implementations • 12 Oct 2023 • Hu Yu, Li Shen, Jie Huang, Man Zhou, Hongsheng Li, Feng Zhao
Diffusion models have demonstrated compelling generation quality by optimizing the variational lower bound through a simple denoising score matching loss.
1 code implementation • 23 Aug 2023 • Hu Yu, Jie Huang, Kaiwen Zheng, Feng Zhao
The latter stage exploits the strong generation ability of DDPM to compensate for the haze-induced huge information loss, by working in conjunction with the physical modelling.
1 code implementation • CVPR 2023 • Jinghao Zhang, Jie Huang, Mingde Yao, Zizheng Yang, Hu Yu, Man Zhou, Feng Zhao
Learning to leverage the relationship among diverse image restoration tasks is quite beneficial for unraveling the intrinsic ingredients behind the degradation.
no code implementations • CVPR 2023 • Zizheng Yang, Jie Huang, Jiahao Chang, Man Zhou, Hu Yu, Jinghao Zhang, Feng Zhao
Deep image recognition models suffer a significant performance drop when applied to low-quality images since they are trained on high-quality images.
1 code implementation • 11 Oct 2022 • Man Zhou, Hu Yu, Jie Huang, Feng Zhao, Jinwei Gu, Chen Change Loy, Deyu Meng, Chongyi Li
Existing convolutional neural networks widely adopt spatial down-/up-sampling for multi-scale modeling.
no code implementations • 14 Jul 2022 • Hu Yu, Jie Huang, Yajing Liu, Qi Zhu, Man Zhou, Feng Zhao
Although certain Domain Adaptation (DA) dehazing methods have been presented, they inevitably require access to the source dataset to reduce the gap between the source synthetic and target real domains.