Don't only Feel Read: Using Scene text to understand advertisements

06/21/2018
by   Arka Ujjwal dey, et al.
0

We propose a framework for automated classification of Advertisement Images, using not just Visual features but also Textual cues extracted from embedded text. Our approach takes inspiration from the assumption that Ad images contain meaningful textual content, that can provide discriminative semantic interpretetion, and can thus aid in classifcation tasks. To this end, we develop a framework using off-the-shelf components, and demonstrate the effectiveness of Textual cues in semantic Classfication tasks.

READ FULL TEXT
research
05/25/2019

Beyond Visual Semantics: Exploring the Role of Scene Text in Image Understanding

Images with visual and scene text content are ubiquitous in everyday lif...
research
02/21/2015

Don't Just Listen, Use Your Imagination: Leveraging Visual Common Sense for Non-Visual Tasks

Artificial agents today can answer factual questions. But they fall shor...
research
05/15/2021

STAGE: Tool for Automated Extraction of Semantic Time Cues to Enrich Neural Temporal Ordering Models

Despite achieving state-of-the-art accuracy on temporal ordering of even...
research
09/21/2020

Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval

Scene text instances found in natural images carry explicit semantic inf...
research
09/02/2019

Know2Look: Commonsense Knowledge for Visual Search

With the rise in popularity of social media, images accompanied by conte...
research
09/17/2021

Including Keyword Position in Image-based Models for Act Segmentation of Historical Registers

The segmentation of complex images into semantic regions has seen a grow...
research
03/18/2021

Learning Multimodal Affinities for Textual Editing in Images

Nowadays, as cameras are rapidly adopted in our daily routine, images of...

Please sign up or login with your details

Forgot password? Click here to reset