activity
20182023
most citedConfidence from Invariance to Image Transformations

15 citations · 48 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV2023★ 4 cited

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…

cs.LG2023

Kissing to Find a Match: Efficient Low-Rank Permutation Representation

Hannah Dröge, Zorah Lähner, Yuval Bahat +3

Permutation matrices play a key role in matching and assignment problems across the fields, especially in computer vision and robotics. However, memory for explicitly representing…

cs.CV2022★ 3 cited

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…

cs.CV2022★ 4 cited

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…

cs.CV2021

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…

cs.CV2020★ 8 cited

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…

eess.IV2020

What's in the Image? Explorable Decoding of Compressed Images

Yuval Bahat, Tomer Michaeli

The ever-growing amounts of visual contents captured on a daily basis necessitate the use of lossy compression methods in order to save storage space and transmission bandwidth. Wh…

cs.CV2019

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…

cs.LG2019★ 14 cited

Natural and Adversarial Error Detection using Invariance to Image Transformations

Yuval Bahat, Michal Irani, Gregory Shakhnarovich

We propose an approach to distinguish between correct and incorrect image classifications. Our approach can detect misclassifications which either occur ("na…

cs.CV2018★ 15 cited

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…