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cs.CV2026
FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows
Daniel Gilo, Sven Elflein, Ido Sobol +1
Conditional diffusion and flow models routinely fail to satisfy the very constraints that define their task. For instance, a depth-conditioned model often produces images whose re-…
cs.GR2026
Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning
Ido Sobol, Kihyuk Sohn, Yoav Blum +4
We often aim to generate images that are both photorealistic and 3D-consistent, adhering to precise geometry, material, and viewpoint controls. Typically, this is achieved by fine-…
cs.CV2026
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…