research
∙
05/02/2019
Billion-scale semi-supervised learning for image classification
This paper presents a study of semi-supervised learning with large convo...
share
research
∙
04/25/2019
Holistic Large Scale Video Understanding
Action recognition has been advanced in recent years by benchmarks with ...
research
∙
12/26/2018
Exploring the Challenges towards Lifelong Fact Learning
So far life-long learning (LLL) has been studied in relatively small-sca...
research
∙
05/02/2018
Exploring the Limits of Weakly Supervised Pretraining
State-of-the-art visual perception models for a wide range of tasks rely...
research
∙
04/27/2018
Large-Scale Visual Relationship Understanding
Large scale visual understanding is challenging, as it requires a model ...
research
∙
12/26/2017
Detect-and-Track: Efficient Pose Estimation in Videos
This paper addresses the problem of estimating and tracking human body k...
research
∙
11/30/2017
A Closer Look at Spatiotemporal Convolutions for Action Recognition
In this paper we discuss several forms of spatiotemporal convolutions fo...
research
∙
05/29/2017
Pose-Aware Person Recognition
Person recognition methods that use multiple body regions have shown sig...
research
∙
05/20/2017
End-to-end Planning of Fixed Millimeter-Wave Networks
This article discusses a framework to support the design and end-to-end ...
research
∙
07/15/2016
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
Modern deep neural networks have a large number of parameters, making th...
research
∙
06/23/2016
VideoMCC: a New Benchmark for Video Comprehension
While there is overall agreement that future technology for organizing, ...
research
∙
11/18/2015
Metric Learning with Adaptive Density Discrimination
Distance metric learning (DML) approaches learn a transformation to a re...
research
∙
11/13/2015
Unsupervised Learning of Edges
Data-driven approaches for edge detection have proven effective and achi...
research
∙
11/12/2015
ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks
This paper aims to classify and locate objects accurately and efficientl...
research
∙
01/23/2015
Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues
We explore the task of recognizing peoples' identities in photo albums i...
research
∙
12/02/2014
Learning Spatiotemporal Features with 3D Convolutional Networks
We propose a simple, yet effective approach for spatiotemporal feature l...
research
∙
06/09/2014
Training Convolutional Networks with Noisy Labels
The availability of large labeled datasets has allowed Convolutional Net...
research
∙
11/21/2013