activity
20142024
most citedThe Role of Redundant Bases and Shrinkage Functions in Image Denoising

8 citations · 19 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2024

SMM-Conv: Scalar Matrix Multiplication with Zero Packing for Accelerated Convolution

Amir Ofir, Gil Ben-Artzi

We present a novel approach for accelerating convolutions during inference for CPU-based architectures. The most common method of computation involves packing the image into the co…

cs.CV2024★ 1 cited

Deep BI-RADS Network for Improved Cancer Detection from Mammograms

Gil Ben-Artzi, Feras Daragma, Shahar Mahpod

While state-of-the-art models for breast cancer detection leverage multi-view mammograms for enhanced diagnostic accuracy, they often focus solely on visual mammography data. Howev…

cs.CV2022

CTrGAN: Cycle Transformers GAN for Gait Transfer

Shahar Mahpod, Noam Gaash, Hay Hoffman +1

We introduce a novel approach for gait transfer from unconstrained videos in-the-wild. In contrast to motion transfer, the objective here is not to imitate the source's motions by…

cs.CV2022

Hypernetwork-Based Adaptive Image Restoration

Shai Aharon, Gil Ben-Artzi

Adaptive image restoration models can restore images with different degradation levels at inference time without the need to retrain the model. We present an approach that is highl…

eess.IV2020★ 1 cited

Adaptive Enhancement of Extreme Low-Light Images

Evgeny Hershkovitch Neiterman, Michael Klyuchka, Gil Ben-Artzi

Existing methods for enhancing dark images captured in a very low-light environment assume that the intensity level of the optimal output image is known and already included in the…

cs.CV2020

Separable Four Points Fundamental Matrix

Gil Ben-Artzi

We present a novel approach for RANSAC-based computation of the fundamental matrix based on epipolar homography decomposition. We analyze the geometrical meaning of the decompositi…

eess.IV2020★ 8 cited

The Role of Redundant Bases and Shrinkage Functions in Image Denoising

Yacov Hel-Or, Gil Ben-Artzi

Wavelet denoising is a classical and effective approach for reducing noise in images and signals. Suggested in 1994, this approach is carried out by rectifying the coefficients of…

cs.CV2017

Camera Calibration by Global Constraints on the Motion of Silhouettes

Gil Ben-Artzi

We address the problem of epipolar geometry using the motion of silhouettes. Such methods match epipolar lines or frontier points across views, which are then used as the set of pu…

cs.CV2016★ 3 cited

Fundamental Matrices from Moving Objects Using Line Motion Barcodes

Yoni Kasten, Gil Ben-Artzi, Shmuel Peleg +1

Computing the epipolar geometry between cameras with very different viewpoints is often very difficult. The appearance of objects can vary greatly, and it is difficult to find corr…

cs.CV2016★ 2 cited

Epipolar Geometry Based On Line Similarity

Gil Ben-Artzi, Tavi Halperin, Michael Werman +1

It is known that epipolar geometry can be computed from three epipolar line correspondences but this computation is rarely used in practice since there are no simple methods to fin…

cs.CV2015★ 2 cited

Camera Calibration from Dynamic Silhouettes Using Motion Barcodes

Gil Ben-Artzi, Yoni Kasten, Shmuel Peleg +1

Computing the epipolar geometry between cameras with very different viewpoints is often problematic as matching points are hard to find. In these cases, it has been proposed to use…

cs.CV2014★ 2 cited

Event Retrieval Using Motion Barcodes

Gil Ben-Artzi, Michael Werman, Shmuel Peleg

We introduce a simple and effective method for retrieval of videos showing a specific event, even when the videos of that event were captured from significantly different viewpoint…