ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences

5 June 2022

Papers citing "ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences"

8 / 8 papers shown

Title
DiffusionAct: Controllable Diffusion Autoencoder for One-shot Face Reenactment Stella Bounareli Christos Tzelepis Vasileios Argyriou Ioannis Patras Georgios Tzimiropoulos DiffM 41 7 0 25 Mar 2024
HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces Stella Bounareli Christos Tzelepis Vasileios Argyriou Ioannis Patras Georgios Tzimiropoulos CVBM 19 35 0 20 Jul 2023
Attribute-preserving Face Dataset Anonymization via Latent Code Optimization Simone Barattin Christos Tzelepis Ioannis Patras N. Sebe PICV CVBM 15 41 0 20 Mar 2023
Bridging CLIP and StyleGAN through Latent Alignment for Image Editing Wanfeng Zheng Qiang Li Xiaoyan Guo Pengfei Wan Zhong-ming Wang 63 14 0 10 Oct 2022
clip2latent: Text driven sampling of a pre-trained StyleGAN using denoising diffusion and CLIP Justin N. M. Pinkney Chuan Li CLIP VLM 37 19 0 05 Oct 2022
WarpedGANSpace: Finding non-linear RBF paths in GAN latent space Christos Tzelepis Georgios Tzimiropoulos Ioannis Patras 71 62 0 27 Sep 2021
Talk-to-Edit: Fine-Grained Facial Editing via Dialog Yuming Jiang Ziqi Huang Xingang Pan Chen Change Loy Ziwei Liu DiffM 107 125 0 09 Sep 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021