activity
20132017
most citedDescribing Videos by Exploiting Temporal Structure

188 citations · 427 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2017★ 5 cited

Action Classification and Highlighting in Videos

Atousa Torabi, Leonid Sigal

Inspired by recent advances in neural machine translation, that jointly align and translate using encoder-decoder networks equipped with attention, we propose an attentionbased LST…

cs.CV2016★ 70 cited

Learning Language-Visual Embedding for Movie Understanding with Natural-Language

Atousa Torabi, Niket Tandon, Leonid Sigal

Learning a joint language-visual embedding has a number of very appealing properties and can result in variety of practical application, including natural language image/video anno…

cs.CV2016★ 5 cited

Movie Description

Anna Rohrbach, Atousa Torabi, Marcus Rohrbach +5

Audio Description (AD) provides linguistic descriptions of movies and allows visually impaired people to follow a movie along with their peers. Such descriptions are by design main…

cs.CV2015★ 159 cited

Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research

Atousa Torabi, Christopher Pal, Hugo Larochelle +1

In this work, we introduce a dataset of video annotated with high quality natural language phrases describing the visual content in a given segment of time. Our dataset is based on…

stat.ML2015★ 188 cited

Describing Videos by Exploiting Temporal Structure

Li Yao, Atousa Torabi, Kyunghyun Cho +4

Recent progress in using recurrent neural networks (RNNs) for image description has motivated the exploration of their application for video description. However, while images are…

cs.CV2013

A Bag of Words Approach for Semantic Segmentation of Monitored Scenes

Wassim Bouachir, Atousa Torabi, Guillaume-Alexandre Bilodeau +1

This paper proposes a semantic segmentation method for outdoor scenes captured by a surveillance camera. Our algorithm classifies each perceptually homogenous region as one of the…