Search Results for author:
Found 17 papers, 9 papers with code
Good News, Everyone! Context driven entity-aware captioning for news images
We propose a novel captioning method that is able to leverage contextual information provided by the text of news articles associated with an image.
Scene Text Visual Question Answering
Current visual question answering datasets do not consider the rich semantic information conveyed by text within an image.
Selective Style Transfer for Text
This paper explores the possibilities of image style transfer applied to text maintaining the original transcriptions.
ICDAR 2019 Competition on Scene Text Visual Question Answering
ST-VQA introduces an important aspect that is not addressed by any Visual Question Answering system up to date, namely the incorporation of scene text to answer questions asked about an image.
Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features
Text contained in an image carries high-level semantics that can be exploited to achieve richer image understanding.
Ranked #1 on
Fine-Grained Image Classification
on Con-Text
Multimodal grid features and cell pointers for Scene Text Visual Question Answering
This paper presents a new model for the task of scene text visual question answering, in which questions about a given image can only be answered by reading and understanding scene text that is present in it.
Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval
Scene text instances found in natural images carry explicit semantic information that can provide important cues to solve a wide array of computer vision problems.
One-shot Compositional Data Generation for Low Resource Handwritten Text Recognition
Low resource Handwritten Text Recognition (HTR) is a hard problem due to the scarce annotated data and the very limited linguistic information (dictionaries and language models).
Localizing Infinity-shaped fishes: Sketch-guided object localization in the wild
This work investigates the problem of sketch-guided object localization (SGOL), where human sketches are used as queries to conduct the object localization in natural images.
Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning
Explaining an image with missing or non-existent objects is known as object bias (hallucination) in image captioning.
Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching
In this work, we propose two metrics that evaluate the degree of semantic relevance of retrieved items, independently of their annotated binary relevance.
LaTr: Layout-Aware Transformer for Scene-Text VQA
Accounting for this, we propose a single objective pre-training scheme that requires only text and spatial cues.
OCR-IDL: OCR Annotations for Industry Document Library Dataset
It is our hope that OCR-IDL can be a starting point for future works on Document Intelligence.
Text-DIAE: A Self-Supervised Degradation Invariant Autoencoders for Text Recognition and Document Enhancement
In this paper, we propose a Text-Degradation Invariant Auto Encoder (Text-DIAE), a self-supervised model designed to tackle two tasks, text recognition (handwritten or scene-text) and document image enhancement.
MUST-VQA: MUltilingual Scene-text VQA
In this paper, we present a framework for Multilingual Scene Text Visual Question Answering that deals with new languages in a zero-shot fashion.
Out-of-Vocabulary Challenge Report
This paper presents final results of the Out-Of-Vocabulary 2022 (OOV) challenge.
Optical Character Recognition
Optical Character Recognition (OCR)
+1
Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipedia
Particularly, a similar Wikimedia image can be used to illustrate different articles, and the produced caption needs to be adapted to a specific context, therefore allowing us to explore the limits of a model to adjust captions to different contextual information.
