Research Area
Year Published

143 Results

February 22, 2017

Automatic Alt-text: Computer-generated Image Descriptions for Blind Users on a Social Network Service

CSCW

This paper covers the design and deployment of an automatic alt-text (AAT), a system that applies computer vision technology to identify faces, objects, and themes from photos to generate photo alt-text for screen reader users on Facebook.

By: Shaomei Wu, Jeffrey Wieland, Omid Farivar, Julie Schiller

December 6, 2016

Population Density Estimation with Deconvolutional Neural Networks

Workshop on Large Scale Computer Vision at NIPS 2016

This work is part of the Internet.org initiative to provide connectivity all over the world. Population density data is helpful in driving a variety of technology decisions, but currently, a microscopic dataset of population doesn’t exist. Current state of the art population density datasets are at ~1000km2 resolution. To create a better dataset, we have obtained 1PB of satellite imagery at 50cm/pixel resolution to feed through our building classification pipeline.

By: Amy Zhang, Xianming Liu, Tobias Tiecke, Andreas Gros

December 6, 2016

Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation

Arxiv

We propose a novel neural network architecture to perform weakly-supervised learning by suppressing irrelevant neuron activations. When applied to a practical challenge of transforming satellite images into a map of settlements and individual buildings it delivers results that show superior performance and efficiency.

By: Xianming Liu, Amy Zhang, Tobias Tiecke, Andreas Gros, Thomas S. Huang

December 5, 2016

Temporally Coherent Completion of Dynamic Video

SIGGRAPH ASIA

We present an automatic video completion algorithm that synthesizes missing regions in videos in a temporally coherent fashion.

By: Jia-Bin Huang, Sing Bing Kang, Narendra Ahuja, Johannes Kopf

December 5, 2016

360◦ Video Stabilization

SIGGRAPH ASIA

We present a hybrid 3D-2D algorithm for stabilizing 360◦ video using a deformable rotation motion model.

By: Johannes Kopf

October 10, 2016

Learning to Refine Object Segments

European Conference on Computer Vision

In this work we propose to augment feedforward nets for object segmentation with a novel top-down refinement approach.

By: Pedro O. Pinheiro, Tsung-Yi Lin, Ronan Collobert, Piotr Dollar

September 18, 2016

A MultiPath Network for Object Detection

BMVC

We test three modifications to the standard Fast R-CNN object detector to determine if they can overcome the object detection challenges in a COCO object detection dataset.

By: Sergey Zagoruyko, Adam Lerer, Tsung-Yi Lin, Pedro O. Pinheiro, Sam Gross, Soumith Chintala, Piotr Dollar

July 25, 2016

Single Image 3D Interpreter Network

European Conference on Computer Vision (ECCV)

In this work, we propose 3D INterpreter Network (3D-INN), an end-to-end framework which sequentially estimates 2D keypoint heatmaps and 3D object structure, trained on both real 2D-annotated images and synthetic 3D data.

By: Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman

June 27, 2016

Unsupervised Learning of Edges

CVPR

Data-driven approaches for edge detection have proven effective and achieve top results on modern benchmarks. However, all current data-driven edge detectors require manual supervision for training in the form of hand-labeled region segments or object boundaries.

By: Yin Li, Manohar Paluri, James M. Rehg, Piotr Dollar

June 18, 2016

Learning Physical Intuition of Block Towers by Example

International Conference on Machine Learning

Wooden blocks are a common toy for infants, allowing them to develop motor skills and gain intuition about the physical behavior of the world. In this paper, we explore the ability of deep feed-forward models to learn such intuitive physics.

By: Adam Lerer, Sam Gross, Rob Fergus