no code implementations • 19 Jun 2024 • Sanketh Vedula, Valentino Maiorca, Lorenzo Basile, Francesco Locatello, Alex Bronstein

We consider the alignment of metric structures formulated as a discrete Gromov-Wasserstein problem and instead of solving the QAP directly, we propose to learn a related well-scalable linear assignment problem (LAP) whose solution is also a minimizer of the QAP.

no code implementations • 28 May 2024 • Daniel Freedman, Eyal Rozenberg, Alex Bronstein

A central problem in quantum mechanics involves solving the Electronic Schrodinger Equation for a molecule or material.

1 code implementation • 9 Apr 2024 • Tamir Shor, Chaim Baskin, Alex Bronstein

In this work, we present a novel algorithm for both breast cancer classification and segmentation.

1 code implementation • 27 Feb 2024 • Gabriele Serussi, Tamir Shor, Tom Hirshberg, Chaim Baskin, Alex Bronstein

Multi-rotor aerial autonomous vehicles (MAVs) primarily rely on vision for navigation purposes.

1 code implementation • 27 Mar 2023 • Tsachi Blau, Roy Ganz, Chaim Baskin, Michael Elad, Alex Bronstein

We show that the proposed method achieves state-of-the-art results and validate our claim through extensive experiments on a variety of defense methods, classifier architectures, and datasets.

1 code implementation • 13 Mar 2023 • Tamir Shor, Tomer Weiss, Dor Noti, Alex Bronstein

Several studies have particularly focused on applying deep learning techniques to learn these acquisition trajectories in order to attain better image reconstruction, rather than using some predefined set of trajectories.

1 code implementation • 17 Jul 2022 • Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex Bronstein, Michael Elad

Deep Neural Networks (DNNs) are highly sensitive to imperceptible malicious perturbations, known as adversarial attacks.

no code implementations • 7 Oct 2021 • Tomer Weiss, Nissim Peretz, Sanketh Vedula, Arie Feuer, Alex Bronstein

Inspired by these successes, in this work, we propose to learn MIMO acquisition parameters in the form of receive (Rx) antenna elements locations jointly with an image neural-network based reconstruction.

no code implementations • 10 Jun 2021 • Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alex Bronstein, Davide Mottin, Panagiotis Karras

In this paper, we transfer the shape-analysis concept of functional maps from the continuous to the discrete case, and treat the graph alignment problem as a special case of the problem of finding a mapping between functions on graphs.

1 code implementation • ICCV 2021 • Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogerio Feris, Leonid Karlinsky

In this work, we focus on the task of Detector-Free WSG (DF-WSG) to solve WSG without relying on a pre-trained detector.

Ranked #1 on Phrase Grounding on Visual Genome

2 code implementations • 19 Mar 2021 • Elad Amrani, Leonid Karlinsky, Alex Bronstein

To guarantee non-degenerate solutions (i. e., solutions where all labels are assigned to the same class) we propose a mathematically motivated variant of the cross-entropy loss that has a uniform prior asserted on the predicted labels.

Ranked #4 on Unsupervised Image Classification on ImageNet

no code implementations • 25 Jan 2021 • Eli Schwartz, Alex Bronstein, Raja Giryes

We then train a model that is applied directly to the RAW data by using knowledge distillation such that the model predictions for RAW images will be aligned with the predictions of an off-the-shelf pre-trained model for processed RGB images.

no code implementations • 26 Nov 2020 • Or Litany, Emanuele Rodolà, Alex Bronstein, Michael Bronstein, Daniel Cremers

We assume to be given a reference shape and its multiple parts undergoing a non-rigid deformation.

1 code implementation • 11 Aug 2020 • Jonathan Alush-Aben, Linor Ackerman-Schraier, Tomer Weiss, Sanketh Vedula, Ortal Senouf, Alex Bronstein

Magnetic Resonance Imaging (MRI) has long been considered to be among the gold standards of today's diagnostic imaging.

no code implementations • 24 Mar 2020 • Amir Livne, Alex Bronstein, Ron Kimmel, Ziv Aviv, Shahaf Grofit

The raw face stereo images along with the location in the image from which the face is extracted allow the proposed CNN to improve the recognition task while avoiding the need to explicitly handle the geometric structure of the face.

1 code implementation • 6 Mar 2020 • Elad Amrani, Rami Ben-Ari, Daniel Rotman, Alex Bronstein

One of the key factors of enabling machine learning models to comprehend and solve real-world tasks is to leverage multimodal data.

Ranked #3 on Visual Question Answering on MSRVTT-QA (Accuracy metric)

1 code implementation • NeurIPS 2020 • Moran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yury Nahshan, Alex Bronstein, Uri Weiser

Neural network quantization methods often involve simulating the quantization process during training, making the trained model highly dependent on the target bit-width and precise way quantization is performed.

no code implementations • 1 Dec 2019 • Sivan Doveh, Eli Schwartz, Chao Xue, Rogerio Feris, Alex Bronstein, Raja Giryes, Leonid Karlinsky

In this work, we propose to employ tools inspired by the Differentiable Neural Architecture Search (D-NAS) literature in order to optimize the architecture for FSL without over-fitting.

1 code implementation • 17 Nov 2019 • Amit Boyarski, Sanketh Vedula, Alex Bronstein

Deep Matrix Factorization (DMF) is an emerging approach to the problem of matrix completion.

no code implementations • 25 Sep 2019 • Amit Boyarski, Sanketh Vedula, Alex Bronstein

We address the problem of reconstructing a matrix from a subset of its entries.

no code implementations • 19 Sep 2019 • Eyal Rozenberg, Daniel Freedman, Alex Bronstein

We present such a technique for localization with limited annotation, in which the number of images with bounding boxes can be a small fraction of the total dataset (e. g. less than 1%); all other images only possess a whole image label and no bounding box.

no code implementations • 13 Sep 2019 • Stefan Sommer, Alex Bronstein

We introduce two constructions in geometric deep learning for 1) transporting orientation-dependent convolutional filters over a manifold in a continuous way and thereby defining a convolution operator that naturally incorporates the rotational effect of holonomy; and 2) allowing efficient evaluation of manifold convolution layers by sampling manifold valued random variables that center around a weighted diffusion mean.

2 code implementations • 12 Sep 2019 • Tomer Weiss, Ortal Senouf, Sanketh Vedula, Oleg Michailovich, Michael Zibulevsky, Alex Bronstein

Such schemes have already demonstrated substantial effectiveness, leading to considerably shorter acquisition times and improved quality of image reconstruction.

2 code implementations • ICLR 2020 • Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alex Bronstein, Ivan Oseledets, Emmanuel Müller

The ability to represent and compare machine learning models is crucial in order to quantify subtle model changes, evaluate generative models, and gather insights on neural network architectures.

1 code implementation • 27 May 2019 • Elad Amrani, Rami Ben-Ari, Tal Hakim, Alex Bronstein

In this work, we propose to exploit the natural correlation in narrations and the visual presence of objects in video, to learn an object detector and retrieval without any manual labeling involved.

1 code implementation • 22 May 2019 • Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg Michailovich, Michael Zibulevsky, Alex Bronstein

On the other hand, recent works in optical computational imaging have demonstrated growing success of the simultaneous learning-based design of the acquisition and reconstruction schemes manifesting significant improvement in the reconstruction quality with a constrained time budget.

no code implementations • 22 May 2019 • Ortal Senouf, Sanketh Vedula, Tomer Weiss, Alex Bronstein, Oleg Michailovich, Michael Zibulevsky

In light of this, we propose a self-supervised approach to training inverse models in medical imaging in the absence of aligned data.

no code implementations • 19 Dec 2018 • Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alex Bronstein, Oleg Michailovich, Michael Zibulevsky

Medical ultrasound (US) is a widespread imaging modality owing its popularity to cost efficiency, portability, speed, and lack of harmful ionizing radiation.

1 code implementation • 6 Dec 2018 • Oshri Halimi, Or Litany, Emanuele Rodolà, Alex Bronstein, Ron Kimmel

The resulting learning model is class-agnostic, and is able to leverage any type of deformable geometric data for the training phase.

no code implementations • 15 Nov 2018 • Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alex Bronstein, Emmanuel Müller

Representing a graph as a vector is a challenging task; ideally, the representation should be easily computable and conducive to efficient comparisons among graphs, tailored to the particular data and analytical task at hand.

1 code implementation • 27 May 2018 • Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alex Bronstein, Emmanuel Müller

However, it is a hard task in terms of the expressiveness of the employed similarity measure and the efficiency of its computation.

Social and Information Networks

no code implementations • CVPR 2018 • Or Litany, Alex Bronstein, Michael Bronstein, Ameesh Makadia

In this work, we propose a novel learning-based method for the completion of partial shapes.

no code implementations • ECCV 2018 • Qiang Qiu, Jose Lezama, Alex Bronstein, Guillermo Sapiro

In this paper, we introduce a random forest semantic hashing scheme that embeds tiny convolutional neural networks (CNN) into shallow random forests, with near-optimal information-theoretic code aggregation among trees.

1 code implementation • 16 Nov 2017 • Gautam Pai, Ronen Talmon, Alex Bronstein, Ron Kimmel

This paper explores a fully unsupervised deep learning approach for computing distance-preserving maps that generate low-dimensional embeddings for a certain class of manifolds.

1 code implementation • 25 Jul 2017 • Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alex Bronstein, Michael Bronstein, Ron Kimmel, Daniel Cremers

We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality.

no code implementations • CVPR 2017 • Matthias Vestner, Roee Litman, Emanuele Rodolà, Alex Bronstein, Daniel Cremers

Many algorithms for the computation of correspondences between deformable shapes rely on some variant of nearest neighbor matching in a descriptor space.

3 code implementations • 15 Dec 2016 • Or Litany, Tal Remez, Alex Bronstein

With the development of range sensors such as LIDAR and time-of-flight cameras, 3D point cloud scans have become ubiquitous in computer vision applications, the most prominent ones being gesture recognition and autonomous driving.

no code implementations • 7 Nov 2016 • Yoni Choukroun, Alon Shtern, Alex Bronstein, Ron Kimmel

Many shape analysis methods treat the geometry of an object as a metric space that can be captured by the Laplace-Beltrami operator.

no code implementations • 18 Sep 2016 • Alex Bronstein, Yoni Choukroun, Ron Kimmel, Matan Sela

The L1 norm has been tremendously popular in signal and image processing in the past two decades due to its sparsity-promoting properties.

no code implementations • 3 Aug 2016 • Tal Remez, Or Litany, Shachar Yoseff, Harel Haim, Alex Bronstein

We present a proof-of-concept end-to-end system for computational extended depth of field (EDOF) imaging.

no code implementations • 12 Jul 2016 • Matthias Vestner, Roee Litman, Alex Bronstein, Emanuele Rodolà, Daniel Cremers

Many algorithms for the computation of correspondences between deformable shapes rely on some variant of nearest neighbor matching in a descriptor space.

no code implementations • 6 Dec 2015 • Or Litany, Tal Remez, Alex Bronstein

Recently, the dense binary pixel Gigavision camera had been introduced, emulating a digital version of the photographic film.

no code implementations • 4 Dec 2015 • Or Litany, Tal Remez, Daniel Freedman, Lior Shapira, Alex Bronstein, Ran Gal

We present ASIST, a technique for transforming point clouds by replacing objects with their semantically equivalent counterparts.

no code implementations • 15 Oct 2015 • Tal Remez, Or Litany, Alex Bronstein

In this work, we study a variant of a sensor with binary threshold pixels and propose a reconstruction algorithm combining an ML data fitting term with a sparse synthesis prior.

no code implementations • 16 Dec 2014 • Qiang Qiu, Guillermo Sapiro, Alex Bronstein

Traditional random forest fails to enforce the consistency of hashes generated from each tree for the same class data, i. e., to preserve the underlying similarity, and it also lacks a principled way for code aggregation across trees.

no code implementations • 29 Jan 2014 • Yonathan Aflalo, Alex Bronstein, Ron Kimmel

We consider the problem of exact and inexact matching of weighted undirected graphs, in which a bijective correspondence is sought to minimize a quadratic weight disagreement.

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