9 papers · 1 filter
RealMaster: Lifting Rendered Scenes into Photorealistic Video
Dana Cohen-Bar, Ido Sobol, Raphael Bensadoun +5
State-of-the-art video generation models produce remarkable photorealism, but they lack the precise control required to align generated content with specific scene requirements. Fu…
Tuning-free Visual Effect Transfer across Videos
Maxwell Jones, Rameen Abdal, Or Patashnik +4
We present RefVFX, a new framework that transfers complex temporal effects from a reference video onto a target video or image in a feed-forward manner. While existing methods exce…
SemanticMoments: Training-Free Motion Similarity via Third Moment Features
Saar Huberman, Kfir Goldberg, Or Patashnik +2
Retrieving videos based on semantic motion is a fundamental, yet unsolved, problem. Existing video representation approaches overly rely on static appearance and scene context rath…
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…