DFANet: Deep Feature Aggregation
2019-07-04 本文已影响0人
Cat丹
旷视新提出的语义分割paper,主要着力点在速度提升上(it achieves 70.3% Mean IOU on the Cityscapes test dataset with only 1.7 GFLOPs and a speed of 160 FPS on one NVIDIA Titan X card, and 71.3% Mean IOU with 3.4 GFLOPs while inferring on a higher resolution image。采用了新的特征聚合方式,sub-network,sub-stage聚合,轻量,且效果不错。github上也有非官方代码复现。
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