DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks

30 Oct 2014 • Tao Chen • Damian Borth • Trevor Darrell • Shih-Fu Chang

This paper introduces a visual sentiment concept classification method based on deep convolutional neural networks (CNNs). The visual sentiment concepts are adjective noun pairs (ANPs) automatically discovered from the tags of web photos, and can be utilized as effective statistical cues for detecting emotions depicted in the images... (read more)

PDF Abstract

Results from the Paper

Edit

Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

METHOD	TYPE
🤖 No Methods Found	Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet

DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Edit

Methods used in the Paper

Add Remove

Edit Social Preview

DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks Edit social preview

Code Edit Add Remove Mark official

Tasks Edit Add Remove

Datasets Edit

Results from the Paper Edit

Methods used in the Paper Edit Add Remove

DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Edit

Methods used in the Paper

Add Remove