Benchmark platform for ultra-fine-grained visual categorization beyond human performance

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Yu, X
Zhao, Y
Gao, Y
Yuan, X
Xiong, S
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2021
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Montreal, QC, Canada

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Abstract

Deep learning methods have achieved remarkable success in fine-grained visual categorization. Such success-fill categorization at sub-ordinate level, e.g., different animal or plant species, however relies heavily on the visual differences that human can observe and the ground-truths are labelled on the basis of such human visual observation. In contrast, few research has been done for visual categorization at the ultra-fine-grained level, i.e., a granularity where even human experts can hardly identify the visual differences or are not yet able to give affirmative labels by inferring observed pattern differences. This paper reports our efforts towards mitigating this research gap. We introduce the ultra-fine-grained (UFG) image dataset, a large collection of 47,114 images from 3,526 categories. All the images in the proposed UFG image dataset are grouped into categories with different confirmed cultivar names. In addition, we perform an extensive evaluation of state-of-the-art fine-grained classification methods on the proposed UFG image dataset as comparative baselines. The proposed UFG image dataset and evaluation protocols is intended to serve as a benchmark platform that can advance research of visual classification from approaching human performance to beyond human ability, via facilitating benchmark data of artificial intelligence (AI) not to be limited by the labels of human intelligence (HI). The dataset is available online at https://gi thub.com/XiaohanYu-GU/Ultra-FGVC.

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Proceedings of the IEEE International Conference on Computer Vision

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© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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Computer vision

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Yu, X; Zhao, Y; Gao, Y; Yuan, X; Xiong, S, Benchmark platform for ultra-fine-grained visual categorization beyond human performance, Proceedings of the IEEE International Conference on Computer Vision, 2021, pp. 10265-10275