The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
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Updated
Nov 17, 2022 - Python
The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
This is an official implementation of facial landmark detection for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
Train the HRNet model on ImageNet
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
Reviving Iterative Training with Mask Guidance for Interactive Segmentation
[CVPR2020] f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation https://arxiv.org/abs/2001.10331
[WACV2021] Foreground-aware Semantic Representations for Image Harmonization https://arxiv.org/abs/2006.00809
Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).
High-resolution Networks for the Fully Convolutional One-Stage Object Detection (FCOS) algorithm
Multi Person Support on HRNets
Reviving Iterative Training with Mask Guidance for Interactive Segmentation.
High-resolution representation learning (HRNets) for Semantic Segmentation
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