4 papers · 1 filter
NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters
Haoran Xu, Xingzhuo Guo, Yuchen Zhang +3
Precipitation nowcasting demands accurate short-term forecasts under strong spatiotemporal variability. Diffusion models are well suited to modeling complex precipitation distribut…
Mitigating the Noise Shift for Denoising Generative Models via Noise Awareness Guidance
Jincheng Zhong, Boyuan Jiang, Xin Tao +3
Existing denoising generative models rely on solving discretized reverse-time SDEs or ODEs. In this paper, we identify a long-overlooked yet pervasive issue in this family of model…
Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model
Jincheng Zhong, Xiangcheng Zhang, Jianmin Wang +1
Recent advancements in diffusion models have revolutionized generative modeling. However, the impressive and vivid outputs they produce often come at the cost of significant model…
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
Jincheng Zhong, Xingzhuo Guo, Jiaxiang Dong +1
Diffusion models have significantly advanced the field of generative modeling. However, training a diffusion model is computationally expensive, creating a pressing need to adapt o…