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

8 October 2022

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

4 / 4 papers shown

Title
IntentTuner: An Interactive Framework for Integrating Human Intents in Fine-tuning Text-to-Image Generative Models Xingchen Zeng Ziyao Gao Yilin Ye Wei Zeng 12 12 0 28 Jan 2024
Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images Hansa Srinivasan Candice Schumann Aradhana Sinha David Madras Gbolahan O. Olanubi Alex Beutel Susanna Ricco Jilin Chen 10 5 0 25 Jan 2024
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,183 0 12 Dec 2018
Inverting The Generator Of A Generative Adversarial Network Antonia Creswell Anil Anthony Bharath GAN 149 337 0 17 Nov 2016