136 citations · 173 across the 5 of their papers we have counts for
5 papers
High-Resolution Image Editing via Multi-Stage Blended Diffusion
Johannes Ackermann, Minjun Li
Diffusion models have shown great results in image generation and in image editing. However, current approaches are limited to low resolutions due to the computational cost of trai…
Surrogate Gradient Field for Latent Space Manipulation
Minjun Li, Yanghua Jin, Huachun Zhu
Generative adversarial networks (GANs) can generate high-quality images from sampled latent codes. Recent works attempt to edit an image by manipulating its underlying latent code,…
Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks
Minjun Li, Haozhi Huang, Lin Ma +3
Recent studies on unsupervised image-to-image translation have made a remarkable progress by training a pair of generative adversarial networks with a cycle-consistent loss. Howeve…
Towards the Automatic Anime Characters Creation with Generative Adversarial Networks
Yanghua Jin, Jiakai Zhang, Minjun Li +3
Automatic generation of facial images has been well studied after the Generative Adversarial Network (GAN) came out. There exists some attempts applying the GAN model to the proble…
Weakly Supervised Dense Video Captioning
Zhiqiang Shen, Jianguo Li, Zhou Su +4
This paper focuses on a novel and challenging vision task, dense video captioning, which aims to automatically describe a video clip with multiple informative and diverse caption s…