Datasets:
license: cc-by-nc-sa-4.0
task_categories:
- visual-question-answering
language:
- en
tags:
- Agriculture
- E-commerce
- Manufacture
- Medical
pretty_name: VisualFastMappingBenchmark
size_categories:
- 1K<n<10K
VisualFastMappingBenchmark
Abstract
Visual Fast Mapping (VFM) refers to the human ability to rapidly form new visual concepts from minimal examples based on experience and knowledge, a keystone of inductive capacity extensively studied in cognitive science. In the realm of computer vision, early endeavors tried to replicate this capability through one-shot learning methods yet achieving limited generalization. Despite the recent advancements in Visual Language Models (VLMs), this human-like capability still has not been acquired. We introduce a novel benchmark, designed to evaluate the VFM ability in realistic industrial scenarios. Our paper and accompanying code will be publicly available online soon.
Benchmark Construction
In the previous years, plenty of high-quality datasets for perception or classification tasks on various domain have been established. Our benchmark mainly focuses on four significant industries, including agriculture, manufacturing, medicine and e-commence, whose tasks require understanding of professional vertical fields. More than 30 thousands concept images from 31 datasets have been collected as the raw data. we employed a three-stage pipeline to curate candidate query images from raw data, ensuring the benchmark's difficulty, diversity, and quality. First, a difficulty filter was applied to exclude samples deemed insufficiently challenging, using five mainstream models as judge. Next, to promote diversity, we utilized a CLIP visual encoder to extract image features, followed by k-means clustering to sample 1,050 representative images per industry. Finally, a manual review ensured the clarity and answerability of the selected queries, resulting in a high-quality, diverse, and appropriately challenging dataset. After the whole process, 4,200 images of 512 concepts by 171 tasks have been collected in VFM Bench, as demonstrated in below Table.
| Industry | Dataset Num. | Task Num. | Concept Num. | Avg. Category Per Task |
|---|---|---|---|---|
| Manufacture | 8 | 1050 | 36 | 110 |
| M-Commerce | 11 | 1050 | 22 | 109 |
| Agriculture | 9 | 1050 | 11 | 48 |
| Medical | 3 | 1050 | 102 | 246 |
Dataset Files Introduction
The test.jsonl file only shows 4020 0-shot data entries. 5-shot example datas can be found in the VisualFastMappingBenchmark.zip file.
Licensing Information
The dataset is distributed under the CC-BY-NC-SA 4.0 license.