9 papers
Continuous Control of Editing Models via Adaptive-Origin Guidance
Alon Wolf, Chen Katzir, Kfir Aberman +1
Diffusion-based editing models have emerged as a powerful tool for semantic image and video manipulation. However, existing models lack a mechanism for smoothly controlling the int…
In-Context Sync-LoRA for Portrait Video Editing
Sagi Polaczek, Or Patashnik, Ali Mahdavi-Amiri +1
Editing portrait videos is a challenging task that requires flexible yet precise control over a wide range of modifications, such as appearance changes, expression edits, or the ad…
DeLeaker: Dynamic Inference-Time Reweighting For Semantic Leakage Mitigation in Text-to-Image Models
Mor Ventura, Michael Toker, Or Patashnik +2
Text-to-Image (T2I) models have advanced rapidly, yet they remain vulnerable to semantic leakage, the unintended transfer of semantically related features between distinct entities…
SAEdit: Token-level control for continuous image editing via Sparse AutoEncoder
Ronen Kamenetsky, Sara Dorfman, Daniel Garibi +3
Large-scale text-to-image diffusion models have become the backbone of modern image editing, yet text prompts alone do not offer adequate control over the editing process. Two prop…
Scaling Group Inference for Diverse and High-Quality Generation
Gaurav Parmar, Or Patashnik, Daniil Ostashev +4
Generative models typically sample outputs independently, and recent inference-time guidance and scaling algorithms focus on improving the quality of individual samples. However, i…
Zero-Shot Dynamic Concept Personalization with Grid-Based LoRA
Rameen Abdal, Or Patashnik, Ekaterina Deyneka +5
Recent advances in text-to-video generation have enabled high-quality synthesis from text and image prompts. While the personalization of dynamic concepts, which capture subject-sp…