444 Results
November 3, 2018
The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments
Conference on Computer-Supported Cooperative Work and Social Computing (CSCW)
Like sighted people, visually impaired people want to share photographs on social networking services, but find it difficult to identify and select photos from their albums. We aimed to address this problem by incorporating state-of-the-art computer-generated descriptions into Facebook’s photo-sharing feature.
By: Yuhang Zhao, Shaomei Wu, Lindsay Reynolds, Shiri Azenkot
Human Computer Interaction & UX July 9, 2018
Continuous Reasoning: Scaling the Impact of Formal Methods
Logic in Computer Science
This paper describes work in continuous reasoning, where formal reasoning about a (changing) codebase is done in a fashion which mirrors the iterative, continuous model of software development that is increasingly practiced in industry. We suggest that advances in continuous reasoning will allow formal reasoning to scale to more programs, and more programmers.
By: Peter O'Hearn
Facebook AI Research 
Systems & Networking June 25, 2018
“I’m Never Happy with What I Write”: Challenges and Strategies of People with Dyslexia on Social Media
International Conference on Web and Social Media
This work studies the experiences, challenges, and strategies of people with dyslexia when using social media. We interviewed 11 people with dyslexia to understand their general experiences with reading and writing content on Facebook. The interview study findings highlight the challenges they face when writing content on Social Networking Sites (SNSs), and their strategies for mitigating these challenges.
By: Lindsay Reynolds, Shaomei WuJune 25, 2018
Do Diffusion Protocols Govern Cascade Growth?
International AAAI Conference on Web and Social Media (ICWSM)
Large cascades can develop in online social networks as people share information with one another. Though simple reshare cascades have been studied extensively, the full range of cascading behaviors on social media is much more diverse. Here we study how diffusion protocols, or the social exchanges that enable information transmission, affect cascade growth, analogous to the way communication protocols define how information is transmitted from one point to another.
By: Justin Cheng, Jon Kleinberg, Jure Leskovec, David Liben-Nowell, Bogdan State, Karthik Subbian, Lada Adamic
Data Science June 18, 2018
Learning to Segment Every Thing
Computer Vision and Pattern Recognition (CVPR)
The goal of this paper is to propose a new partially supervised training paradigm, together with a novel weight transfer function, that enables training instance segmentation models on a large set of categories all of which have box annotations, but only a small fraction of which have mask annotations.
By: Ronghang Hu, Piotr Dollar, Kaiming He, Trevor Darrell, Ross Girshick
Computer Vision June 18, 2018
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation
Computer Vision and Pattern Recognition (CVPR)
In this work we introduce a time- and memory-efficient method for structured prediction that couples neuron decisions across both space at time. We show that we are able to perform exact and efficient inference on a densely connected spatio-temporal graph by capitalizing on recent advances on deep Gaussian random fields.
By: Siddhartha Chandra, Camille Couprie, Iasonas KokkinosJune 18, 2018
Separating Self-Expression and Visual Content in Hashtag Supervision
Computer Vision and Pattern Recognition (CVPR)
This paper presents an approach that extends upon modeling simple image-label pairs with a joint model of images, hashtags, and users. We demonstrate the efficacy of such approaches in image tagging and retrieval experiments, and show how the joint model can be used to perform user-conditional retrieval and tagging.
By: Andreas Veit, Maximilian Nickel, Serge Belongie, Laurens van der MaatenJune 18, 2018
Detect-and-Track: Efficient Pose Estimation in Videos
Computer Vision and Pattern Recognition (CVPR)
This paper addresses the problem of estimating and tracking human body keypoints in complex, multi-person video. We propose an extremely lightweight yet highly effective approach that builds upon the latest advancements in human detection [17] and video understanding [5].
By: Rohit Girdhar, Georgia Gkioxari, Lorenzo Torresani, Manohar Paluri, Du Tran
Machine Learning June 18, 2018
Learning by Asking Questions
Computer Vision and Pattern Recognition (CVPR)
We introduce an interactive learning framework for the development and testing of intelligent visual systems, called learning-by-asking (LBA). We explore LBA in context of the Visual Question Answering (VQA) task.
By: Ishan Misra, Ross Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der MaatenJune 18, 2018
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
Computer Vision and Pattern Recognition (CVPR)
We introduce new sparse convolutional operations that are designed to process spatially-sparse data more efficiently, and use them to develop spatially-sparse convolutional networks.
By: Benjamin Graham, Laurens van der Maaten, Martin Engelcke