12 citations · 16 across the 7 of their papers we have counts for
3 papers · 1 filter
When Text-to-Image Helps Editing: The Effects of Conditioning During Denoising
Lidia Troeshestova, Alexander Ustyuzhanin, Sergey Kastryulin
Unified models are trained for both instruction-based image editing and text-to-image (T2I) generation, but standard editing pipelines keep source-image conditioning throughout den…
Revisiting Classifier-Free Guidance Methods in Latent Diffusion Models
Artem Sergievskii, Artyom Turevich, Sergey Kastryulin
Inference-time quality-enhancement methods are an effective and widely adopted means of improving diffusion models without expensive retraining. We study a family of training-free…
DuET: Dual Expert Trajectories for Diffusion Image Editing
Lidia Troeshestova, Alexander Ustyuzhanin, Sergey Kastryulin
Recent diffusion editors perform diverse instruction-based edits while conditioning on the source image at every denoising step. Yet persistent source-image conditioning can limit…