High-Resolution Representations for Labeling Pixels and Regions

9 Apr 2019Ke SunYang ZhaoBorui JiangTianheng ChengBin XiaoDong LiuYadong MuXinggang WangWenyu LiuJingdong Wang

High-resolution representation learning plays an essential role in many vision problems, e.g., pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite{SunXLW19}, recently developed for human pose estimation, maintains high-resolution representations through the whole process by connecting high-to-low resolution convolutions in \emph{parallel} and produces strong high-resolution representations by repeatedly conducting fusions across parallel convolutions... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Semantic Segmentation ADE20K HRNetV2 Validation mIoU 43.2 # 4