Search Results for author: Simon Korman

Found 12 papers, 5 papers with code

Unsupervised Representation Learning by Balanced Self Attention Matching

1 code implementation4 Aug 2024 Daniel Shalam, Simon Korman

Many leading self-supervised methods for unsupervised representation learning, in particular those for embedding image features, are built on variants of the instance discrimination task, whose optimization is known to be prone to instabilities that can lead to feature collapse.

Representation Learning Self-Supervised Image Classification +2

SeaThru-NeRF: Neural Radiance Fields in Scattering Media

1 code implementation CVPR 2023 Deborah Levy, Amit Peleg, Naama Pearl, Dan Rosenbaum, Derya Akkaynak, Simon Korman, Tali treibitz

Even more excitingly, we can render clear views of these scenes, removing the medium between the camera and the scene and reconstructing the appearance and depth of far objects, which are severely occluded by the medium.

NAN: Noise-Aware NeRFs for Burst-Denoising

no code implementations CVPR 2022 Naama Pearl, Tali treibitz, Simon Korman

Such assumptions are not realistic in the presence of large motion and high levels of noise.

Denoising

The Self-Optimal-Transport Feature Transform

1 code implementation6 Apr 2022 Daniel Shalam, Simon Korman

The Self-Optimal-Transport (SOT) feature transform is designed to upgrade the set of features of a data instance to facilitate downstream matching or grouping related tasks.

Few-Shot Image Classification Large-Scale Person Re-Identification

Generative Adversarial Networks via a Composite Annealing of Noise and Diffusion

no code implementations1 May 2021 Kensuke Nakamura, Simon Korman, Byung-Woo Hong

Based on these observations, we propose a data representation for the GAN training, called noisy scale-space (NSS), that recursively applies the smoothing with a balanced noise to data in order to replace the high-frequency information by random data, leading to a coarse-to-fine training of GANs.

Generative Adversarial Network

OATM: Occlusion Aware Template Matching by Consensus Set Maximization

no code implementations CVPR 2018 Simon Korman, Mark Milam, Stefano Soatto

We present a novel approach to template matching that is efficient, can handle partial occlusions, and comes with provable performance guarantees.

Template Matching

Latent RANSAC

1 code implementation CVPR 2018 Simon Korman, Roee Litman

We present a method that can evaluate a RANSAC hypothesis in constant time, i. e. independent of the size of the data.

3D Face Alignment 3D Plane Detection +4

Deleting and Testing Forbidden Patterns in Multi-Dimensional Arrays

no code implementations13 Jul 2016 Omri Ben-Eliezer, Simon Korman, Daniel Reichman

For any $\epsilon \in [0, 1]$ and any large enough pattern $P$ over any alphabet, other than a very small set of exceptional patterns, we design a tolerant tester that distinguishes between the case that the distance is at least $\epsilon$ and the case that it is at most $a_d \epsilon$, with query complexity and running time $c_d \epsilon^{-1}$, where $a_d < 1$ and $c_d$ depend only on $d$.

LEMMA Open-Ended Question Answering

Peeking Template Matching for Depth Extension

no code implementations ICCV 2015 Simon Korman, Eyal Ofek, Shai Avidan

We demonstrate on real-world data that our algorithm is capable of completing a full 3D scene from a single depth image and can synthesize a full depth map from a novel viewpoint of the scene.

Template Matching

FasT-Match: Fast Affine Template Matching

no code implementations CVPR 2013 Simon Korman, Daniel Reichman, Gilad Tsur, Shai Avidan

Fast-Match is a fast algorithm for approximate template matching under 2D affine transformations that minimizes the Sum-of-Absolute-Differences (SAD) error measure.

Template Matching

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