This is an official implementation of semantic segmentation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h). This is an official implementation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
In your provided annotation file face_landmarks_wflw_test.csv, how are the annotations for "scale", "center_w" and "center_h" computed from the original face bounding box annotations of <x_min, y_min, x_max, y_max> for the face bounding provided by the authors of the WFLW dataset? Could you explain?
In your provided annotation file face_landmarks_wflw_test.csv, how are the annotations for "scale", "center_w" and "center_h" computed from the original face bounding box annotations of <x_min, y_min, x_max, y_max> for the face bounding provided by the authors of the WFLW dataset? Could you explain?