Search Results for author: Amir Bar

Found 15 papers, 8 papers with code

Predicting masked tokens in stochastic locations improves masked image modeling

no code implementations31 Jul 2023 Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann Lecun

Specifically, we condition the model on stochastic masked token positions to guide the model toward learning features that are more robust to location uncertainties.

Language Modelling Masked Language Modeling +3

Visual Prompting via Image Inpainting

1 code implementation1 Sep 2022 Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, Alexei A. Efros

How does one adapt a pre-trained visual model to novel downstream tasks without task-specific finetuning or any model modification?

Colorization Edge Detection +6

Structured Video Tokens @ Ego4D PNR Temporal Localization Challenge 2022

no code implementations15 Jun 2022 Elad Ben-Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach, Leonid Karlinsky, Trevor Darrell, Amir Globerson

First, as both images and videos contain structured information, we enrich a transformer model with a set of \emph{object tokens} that can be used across images and videos.

Point- of-no-return (PNR) temporal localization Temporal Localization

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens

no code implementations13 Jun 2022 Elad Ben-Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach, Leonid Karlinsky, Trevor Darrell, Amir Globerson

We explore a particular instantiation of scene structure, namely a \emph{Hand-Object Graph}, consisting of hands and objects with their locations as nodes, and physical relations of contact/no-contact as edges.

Action Recognition Video Understanding

Object-Region Video Transformers

1 code implementation CVPR 2022 Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson

In this work, we present Object-Region Video Transformers (ORViT), an \emph{object-centric} approach that extends video transformer layers with a block that directly incorporates object representations.

Action Detection Few-Shot action recognition +2

3D Convolutional Sequence to Sequence Model for Vertebral Compression Fractures Identification in CT

no code implementations8 Oct 2020 David Chettrit, Tomer Meir, Hila Lebel, Mila Orlovsky, Ronen Gordon, Ayelet Akselrod-Ballin, Amir Bar

An osteoporosis-related fracture occurs every three seconds worldwide, affecting one in three women and one in five men aged over 50.


Compositional Video Synthesis with Action Graphs

1 code implementation27 Jun 2020 Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson

Our generative model for this task (AG2Vid) disentangles motion and appearance features, and by incorporating a scheduling mechanism for actions facilitates a timely and coordinated video generation.

Scheduling Video Generation +2

Improved ICH classification using task-dependent learning

no code implementations29 Jun 2019 Amir Bar, Michal Mauda, Yoni Turner, Michal Safadi, Eldad Elnekave

Head CT is one of the most commonly performed imaging studied in the Emergency Department setting and Intracranial hemorrhage (ICH) is among the most critical and timesensitive findings to be detected on Head CT. We present BloodNet, a deep learning architecture designed for optimal triaging of Head CTs, with the goal of decreasing the time from CT acquisition to accurate ICH detection.

Classification General Classification

PHT-bot: Deep-Learning based system for automatic risk stratification of COPD patients based upon signs of Pulmonary Hypertension

no code implementations28 May 2019 David Chettrit, Orna Bregman Amitai, Itamar Tamir, Amir Bar, Eldad Elnekave

Secondary pulmonary hypertension is a manifestation of advanced COPD, which can be reliably diagnosed by the main Pulmonary Artery (PA) to Ascending Aorta (Ao) ratio.

Computed Tomography (CT)

Compression Fractures Detection on CT

no code implementations6 Jun 2017 Amir Bar, Lior Wolf, Orna Bergman Amitai, Eyal Toledano, Eldad Elnekave

Finally a Recurrent Neural Network (RNN) is utilized to predict whether a vertebral fracture is present in the series of patches.

Computed Tomography (CT)

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