Amir Bar

I am a first-year Ph.D. student at Tel Aviv University and a visiting student at Berkeley AI Research working with Amir Globerson and Trevor Darrell. My goal is to develop structured representations that can be used to understand videos and real world spatio-temporal dynamics.

I am also an AI Research Lead at Zebra Medical Vision, where I lead the development of CT algorithms. Two of my team's algorithms are FDA approved and adopted at hospitals around the world.

Email  /  Twitter  /  GitHub  /  Google Scholar  /  LinkedIn

ML Publications

Compositional Video Synthesis with Action Graphs    
Amir Bar*, Roei Herzig*, Xiaolong Wang, Gal Chechik, Trevor Darrell, Amir Globerson
arXiv, 2020
Project Page | Code | Video

We introduce Action Graphs, a structure that can better capture the compositional and hierrchical nature of actions. We propose a goal-oriented video synthesis task of *Action Graph to Video*

* Equally contributed.

Learning Canonical Representations for Scene Graph to Image Generation
Roei Herzig*, Amir Bar*, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson
ECCV, 2020
Project Page | Code | Video

We present a model for Scene Graph to Image generation which is more robust to complex input scene graphs.

* Equally contributed.

Learning Individual Styles of Conversational Gesture  
Shiry Ginosar*, Amir Bar*, Gefen Kohavi, Caroline Chan, Andrew Owens, Jitendra Malik
CVPR, 2019
Press | Project Page | Code | Data

We predict plausible gestures to go along with someone's speech.

* Equally contributed.

Sample:

The man allowed that about health captain played that alleged to Marks live up in the club comes the handed up moved to a brief

Language Generation with Recurrent Generative Adversarial Networks without Pre-training
Ofir Press*, Amir Bar*, Ben Bogin*, Jonathan Berant, Lior Wolf
1st Workshop on Learning to Generate Natural Language at ICML, 2017
Code

We show that recurrent neural networks can be trained to generate text with GANs from scratch and vastly improve the quality of generated sequences compared to a convolutional baseline.

* Equally contributed.
Medical Publications

3D Convolutional Sequence to Sequence Model for Vertebral Compression Fractures Identification in CT    
David Chettrit, Tomer Meir, Hila Lebel, Mila Orlovsky, Ronen Gordon, Ayelet Akselrod-Ballin**, Amir Bar**
MICCAI, 2020
Press 1 2

We present a novel architecture used to detect vertebral compression fractures in Chest and Abdomen CT.

** Equally advised.

Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in FRAX underutilization    
Noa Dagan, Eldad Elnekave, Noam Barda, Orna Bregman-Amitai, Amir Bar, Mila Orlovsky, Eitan Bachmat & Ran D. Balicer
Nature Medicine, 2020
Press 1 2

Methods for identifying patients at high risk for osteoporotic fractures are underutilized. We demonstrate it is feasibile to automatically evaluate risk based on routine abdomen or chest computed tomography (CT) scan.

Improved ICH classification using task-dependent learning  
Amir Bar, Michal Mauda-Havakuk, Yoni Turner, Michal Safadi, Eldad Elnekave
ISBI, 2019
Press

Intracranial hemorrhage (ICH) is among the most critical and timesensitive findings to be detected on Head CT. We present a new architecture designed for optimal triaging of Head CTs, with the goal of decreasing the time from CT acquisition to accurate ICH detection. These results are comparable to previously reported results with smaller number of tagged studies.

Simulating Dual-Energy X-Ray Absorptiometry in CT Using Deep-Learning Segmentation Cascade
Arun Krishnaraj, Spencer Barrett, Orna Bregman-Amitai , Michael Cohen-Sfady, Amir Bar, David Chettrit, Mila Orlovsky, Eldad Elnekave
Journal of the American College of Radiology, 2019

Osteoporosis is an underdiagnosed condition despite effective screening modalities. The purpose of this study was to describe a method to simulate lumbar DEXA scores from routinely acquired CT studies using a machine-learning algorithm.

PHT-bot: a deep learning based system for automatic risk stratification of COPD patients based upon signs of pulmonary hypertension
David Chettrit, Orna Bregman Amitai, Itamar Tamir, Amir Bar and Eldad Elnekave
SPIE, 2019

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality worldwide. We apply deep learning algorithm to detect those at risk.

Compression Fractures Detection on CT
Amir Bar, Lior Wolf, Orna Bregman Amitai, Eyal Toledano, Eldad Elnekave
SPIE, 2017
Press 1 2

The presence of a vertebral compression fracture is highly indicative of osteoporosis and represents the single most robust predictor for development of a second osteoporotic fracture in the spine or elsewhere. We present an automated method for detecting spine compression fractures in Computed Tomography (CT) scans.

Misc

Meet my dog taco on instagram :)


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