TDIUC

Task Directed Image Understanding Challenge

Dataset Information
Modalities
Images
Introduced
2017
License
Unknown
Homepage

Overview

Task Directed Image Understanding Challenge (TDIUC) dataset is a Visual Question Answering dataset which consists of 1.6M questions and 170K images sourced from MS COCO and the Visual Genome Dataset. The image-question pairs are split into 12 categories and 4 additional evaluation matrices which help evaluate models’ robustness against answer imbalance and its ability to answer questions that require higher reasoning capability. The TDIUC dataset divides the VQA paradigm into 12 different task directed question types. These include questions that require a simpler task (e.g., object presence, color attribute) and more complex tasks (e.g., counting, positional reasoning). The dataset includes also an “Absurd” question category in which questions are irrelevant to the image contents to help balance the dataset.

Source: Question-Agnostic Attention for Visual Question Answering
Image Source: https://kushalkafle.com/projects/tdiuc.html

Variants: TDIUC

Associated Benchmarks

This dataset is used in 1 benchmark:

Recent Benchmark Submissions

Task Model Paper Date
Visual Question Answering (VQA) BAN2-CTI Compact Trilinear Interaction for Visual … 2019-09-26
Visual Question Answering (VQA) Accuracy MUREL: Multimodal Relational Reasoning for … 2019-02-25

Research Papers

Recent papers with results on this dataset: