1 code implementation • 25 Jan 2024 • Nisha Huang, WeiMing Dong, Yuxin Zhang, Fan Tang, Ronghui Li, Chongyang Ma, Xiu Li, Changsheng Xu
Large-scale text-to-image generative models have made impressive strides, showcasing their ability to synthesize a vast array of high-quality images.
1 code implementation • 8 Dec 2023 • Yuxin Zhang, Fan Tang, Nisha Huang, Haibin Huang, Chongyang Ma, WeiMing Dong, Changsheng Xu
The essence of a video lies in its dynamic motions, including character actions, object movements, and camera movements.
3 code implementations • 25 May 2023 • Yuxin Zhang, WeiMing Dong, Fan Tang, Nisha Huang, Haibin Huang, Chongyang Ma, Tong-Yee Lee, Oliver Deussen, Changsheng Xu
We apply ProSpect in various personalized attribute-aware image generation applications, such as image-guided or text-driven manipulations of materials, style, and layout, achieving previously unattainable results from a single image input without fine-tuning the diffusion models.
1 code implementation • 9 May 2023 • Nisha Huang, Yuxin Zhang, WeiMing Dong
Large-scale text-to-video diffusion models have demonstrated an exceptional ability to synthesize diverse videos.
1 code implementation • 23 Feb 2023 • Nisha Huang, Fan Tang, WeiMing Dong, Tong-Yee Lee, Changsheng Xu
Different from current mask-based image editing methods, we propose a novel region-aware diffusion model (RDM) for entity-level image editing, which could automatically locate the region of interest and replace it following given text prompts.
1 code implementation • CVPR 2023 • Yuxin Zhang, Nisha Huang, Fan Tang, Haibin Huang, Chongyang Ma, WeiMing Dong, Changsheng Xu
Our key idea is to learn artistic style directly from a single painting and then guide the synthesis without providing complex textual descriptions.
1 code implementation • 19 Nov 2022 • Nisha Huang, Yuxin Zhang, Fan Tang, Chongyang Ma, Haibin Huang, Yong Zhang, WeiMing Dong, Changsheng Xu
Despite the impressive results of arbitrary image-guided style transfer methods, text-driven image stylization has recently been proposed for transferring a natural image into a stylized one according to textual descriptions of the target style provided by the user.
1 code implementation • 27 Sep 2022 • Nisha Huang, Fan Tang, WeiMing Dong, Changsheng Xu
Extensive experimental results on the quality and quantity of the generated digital art paintings confirm the effectiveness of the combination of the diffusion model and multimodal guidance.