4 citations · 14 across the 38 of their papers we have counts for
3 papers · 1 filter
CONFORM: Contrast is All You Need For High-Fidelity Text-to-Image Diffusion Models
Tuna Han Salih Meral, Enis Simsar, Federico Tombari +1
Images produced by text-to-image diffusion models might not always faithfully represent the semantic intent of the provided text prompt, where the model might overlook or entirely…
NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions in Diffusion Models
Yusuf Dalva, Pinar Yanardag
Generative models have been very popular in the recent years for their image generation capabilities. GAN-based models are highly regarded for their disentangled latent space, whic…
RAVE: Randomized Noise Shuffling for Fast and Consistent Video Editing with Diffusion Models
Ozgur Kara, Bariscan Kurtkaya, Hidir Yesiltepe +2
Recent advancements in diffusion-based models have demonstrated significant success in generating images from text. However, video editing models have not yet reached the same leve…