Non-local Neural Networks

CVPR 2018 Xiaolong WangRoss GirshickAbhinav GuptaKaiming He

Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family of building blocks for capturing long-range dependencies... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Keypoint Detection COCO Mask R-CNN + NL blocks (4 in head, 1 in backbone) Validation AP 66.5 # 7
Object Detection COCO minival Mask R-CNN (ResNet-101 + 1 NL) box AP 40.8 # 33
Object Detection COCO minival Mask R-CNN (ResNet-101 + 1 NL) AP50 63.1 # 5
Object Detection COCO minival Mask R-CNN (ResNet-101 + 1 NL) AP75 44.5 # 15
Object Detection COCO minival Mask R-CNN (ResNet-50 + 1 NL) box AP 39 # 39
Object Detection COCO minival Mask R-CNN (ResNet-50 + 1 NL) AP50 61.1 # 13
Object Detection COCO minival Mask R-CNN (ResNet-50 + 1 NL) AP75 41.9 # 24
Object Detection COCO minival Mask R-CNN (ResNeXt-152 + 1 NL) box AP 45.0 # 11
Object Detection COCO minival Mask R-CNN (ResNeXt-152 + 1 NL) AP50 67.8 # 1
Object Detection COCO minival Mask R-CNN (ResNeXt-152 + 1 NL) AP75 48.9 # 5
Instance Segmentation COCO minival Mask R-CNN (ResNet-101, +1 NL) mask AP 37.1 # 9
Instance Segmentation COCO minival Mask R-CNN (ResNet-50, +1 NL) mask AP 35.5 # 12
Instance Segmentation COCO minival Mask R-CNN (ResNext-152, +1 NL) mask AP 40.3 # 4