Disentangled Non-Local Neural Networks

The non-local block is a popular module for strengthening the context modeling ability of a regular convolutional neural network. This paper first studies the non-local block in depth, where we find that its attention computation can be split into two terms, a whitened pairwise term accounting for the relationship between two pixels and a unary term representing the saliency of every pixel... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Semantic Segmentation ADE20K val DNL mIoU 45.97 # 7
Semantic Segmentation Cityscapes test DNL (ours) Mean IoU (class) 83% # 10
Semantic Segmentation PASCAL Context DNL mIoU 55.3 # 7

Methods used in the Paper