Research paper · 2018-10-29
TallyQA: Answering Complex Counting Questions
Manoj Acharya, Kushal Kafle, Christopher Kanan
Published2018-10-29
Authors3
Citing Models3
arXiv1810.12440
Abstract
Most counting questions in visual question answering (VQA) datasets are simple and require no more than object detection. Here, we study algorithms for complex counting questions that involve relationships between objects, attribute identification, reasoning, and more. To do this, we created TallyQA, the world's largest dataset for open-ended counting. We propose a new algorithm for counting that uses relation networks with region proposals. Our method lets relation networks be efficiently used with high-resolution imagery. It yields state-of-the-art results compared to baseline and recent systems on both TallyQA and the HowMany-QA benchmark.
Details
- arXiv identifier
- 1810.12440
- Published
- 2018-10-29
- Authors
- Manoj Acharya, Kushal Kafle, Christopher Kanan
Models That Cite This Paper
- Described bygemma-3-1b-it
- Described bygemma-3-4b-it
- Described bygemma-3-27b-it-int4-awq