ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network

We introduce a light-weight, power efficient, and general purpose convolutional neural network, ESPNetv2, for modeling visual and sequential data. Our network uses group point-wise and depth-wise dilated separable convolutions to learn representations from a large effective receptive field with fewer FLOPs and parameters... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Semantic Segmentation Cityscapes test ESPNetv2 Mean IoU (class) 66.2% # 58
Object Detection COCO test-dev ESPNetv2-512 box AP 26.0 # 89
Image Classification ImageNet ESPNetv2 Top 1 Accuracy 74.9% # 129
Object Detection PASCAL VOC 2007 ESPNetv2-512 MAP 68.2% # 27
Semantic Segmentation PASCAL VOC 2012 test ESPNetv2 Mean IoU 68.0% # 33

Methods used in the Paper