Do humans and machines have the same eyes? Human-machine perceptual differences on image classification

• URL: http://arxiv.org/abs/2304.08733v1
• Date: Tue, 18 Apr 2023 05:09:07 GMT
• Title: Do humans and machines have the same eyes? Human-machine perceptual differences on image classification
• Authors: Minghao Liu, Jiaheng Wei, Yang Liu, James Davis
• Abstract summary: Trained computer vision models are assumed to solve vision tasks by imitating human behavior learned from training labels. Our study first quantifies and analyzes the statistical distributions of mistakes from the two sources. We empirically demonstrate a post-hoc human-machine collaboration that outperforms humans or machines alone.
• Score: 8.474744196892722
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Trained computer vision models are assumed to solve vision tasks by imitating human behavior learned from training labels. Most efforts in recent vision research focus on measuring the model task performance using standardized benchmarks. Limited work has been done to understand the perceptual difference between humans and machines. To fill this gap, our study first quantifies and analyzes the statistical distributions of mistakes from the two sources. We then explore human vs. machine expertise after ranking tasks by difficulty levels. Even when humans and machines have similar overall accuracies, the distribution of answers may vary. Leveraging the perceptual difference between humans and machines, we empirically demonstrate a post-hoc human-machine collaboration that outperforms humans or machines alone.

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