Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

ICCV 2017 Chen SunAbhinav ShrivastavaSaurabh SinghAbhinav Gupta

The success of deep learning in vision can be attributed to: (a) models with high capacity; (b) increased computational power; and (c) availability of large-scale labeled data. Since 2012, there have been significant advances in representation capabilities of the models and computational capabilities of GPUs... (read more)

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Evaluation results from the paper

Task Dataset Model Metric name Metric value Global rank Uses extra
training data
Image Classification ImageNet JFT-300M Finetuning Top 1 Accuracy 79.2% # 36
Image Classification ImageNet JFT-300M Finetuning Top 5 Accuracy 94.7% # 31
Semantic Segmentation PASCAL VOC 2012 ImageNet+JFT-300M Initialization Mean IoU 76.5% # 15