15 citations · 48 across the 8 of their papers we have counts for
7 papers · 1 filter
From Posterior Sampling to Meaningful Diversity in Image Restoration
Noa Cohen, Hila Manor, Yuval Bahat +1
Image restoration problems are typically ill-posed in the sense that each degraded image can be restored in infinitely many valid ways. To accommodate this, many works generate a d…
Neural Volume Super-Resolution
Yuval Bahat, Yuxuan Zhang, Hendrik Sommerhoff +2
Neural volumetric representations have become a widely adopted model for radiance fields in 3D scenes. These representations are fully implicit or hybrid function approximators of…
Diffusion-SDF: Conditional Generative Modeling of Signed Distance Functions
Gene Chou, Yuval Bahat, Felix Heide
Probabilistic diffusion models have achieved state-of-the-art results for image synthesis, inpainting, and text-to-image tasks. However, they are still in the early stages of gener…
Neural Point Light Fields
Julian Ost, Issam Laradji, Alejandro Newell +2
We introduce Neural Point Light Fields that represent scenes implicitly with a light field living on a sparse point cloud. Combining differentiable volume rendering with learned im…
Classification Confidence Estimation with Test-Time Data-Augmentation
Yuval Bahat, Gregory Shakhnarovich
Machine learning plays an increasingly significant role in many aspects of our lives (including medicine, transportation, security, justice and other domains), making the potential…
Explorable Super Resolution
Yuval Bahat, Tomer Michaeli
Single image super resolution (SR) has seen major performance leaps in recent years. However, existing methods do not allow exploring the infinitely many plausible reconstructions…
Confidence from Invariance to Image Transformations
Yuval Bahat, Gregory Shakhnarovich
We develop a technique for automatically detecting the classification errors of a pre-trained visual classifier. Our method is agnostic to the form of the classifier, requiring acc…