most citedCLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation

1 citations · 1 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CV2022★ 1 cited

CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation

Chenliang Zhou, Fangcheng Zhong, Cengiz Oztireli

Recently introduced Contrastive Language-Image Pre-Training (CLIP) bridges images and text by embedding them into a joint latent space. This opens the door to ample literature that…