Adaptive Context Network for Scene Parsing

ICCV 2019 Jun Fu Jing Liu Yuhang Wang Yong Li Yongjun Bao Jinhui Tang Hanqing Lu

Recent works attempt to improve scene parsing performance by exploring different levels of contexts, and typically train a well-designed convolutional network to exploit useful contexts across all pixels equally. However, in this paper, we find that the context demands are varying from different pixels or regions in each image... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Semantic Segmentation ADE20K val ACNet (ResNet-101) mIoU 45.90% # 2