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A Study on Synthesizing Training Data for One-stage Object Detector

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Academic year: 2021

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-coca cola coffee mate honey bunches hunt’s sauce mahatma rice nature v1 nature v2 palmolive orange pop secret pringles bbq red bull mAP No augmentation 82.9 93.7 90.5 85.8 90.5 97.2 86.5 88.9 89.7 89.4 71.6 87.9 No blending 84.7 94.3 91.7 87.5 88.9 96.7 86.6 88.1 90.8 90.1 61.2 88.1 Box blurring 84.5 95.5 92.1 87.5 89.1 96.8 87.3 87.5 88.3 90.6 69.3 88.0 Gaussian blurring 83.9 93.8 82.2 88.0 91.0 96.8 87.7 88.8 90.3 89.9 69.7 88.5 Poisson 84.1 95.0 91.2 87.6 86.5 97.1 87.1 88.5 91.3 89.7 71.0 88.1 Ours 83.9 95.1 91.6 88.7 88.6 97.3 88.6 88.7 91.8 91.2 70.8 88.7 Georgios’s [2] 82.6 92.9 91.4 85.5 81.9 95.5 88.6 78.5 93.6 90.2 54.1 85.0 Dwibedi’s [3] 88.5 95.5 94.1 88.1 90.3 97.2 91.8 80.1 94.0 92.2 65.4 88.8 < 1>

449

-2020 온라인 춘계학술발표대회 논문집 제27권 제1호 (-2020. 5)

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