DensePose: Dense Human Pose Estimation In The Wild

CVPR 2018 Rıza Alp GülerNatalia NeverovaIasonas Kokkinos

In this work, we establish dense correspondences between RGB image and a surface-based representation of the human body, a task we refer to as dense human pose estimation. We first gather dense correspondences for 50K persons appearing in the COCO dataset by introducing an efficient annotation pipeline... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Pose Estimation DensePose-COCO DensePose + keypoints AP 55.8 # 2

Methods used in the Paper


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