Swin-Transformer-Semantic-Segmentation
SeMask-Segmentation
| Swin-Transformer-Semantic-Segmentation | SeMask-Segmentation | |
|---|---|---|
| 1 | 2 | |
| 1,081 | 243 | |
| 0.0% | 1.6% | |
| 0.0 | 2.8 | |
| over 1 year ago | 7 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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Swin-Transformer-Semantic-Segmentation
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[P] Code and pretrained models for Swin Transformer are released (SOTA models on COCO and ADE20K)
Semantic segmentation on ADE20K: https://github.com/SwinTransformer/Swin-Transformer-Semantic-Segmentation
SeMask-Segmentation
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Researchers Introduce ‘SeMask’: An Effective Transformer-Framework That Incorporates Semantic Information Into The Encoder With The Help Of A Semantic Attention Operation
Paper: https://arxiv.org/abs/2112.12782
Github: https://github.com/Picsart-AI-Research/SeMask-Segmentation
What are some alternatives?
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Real-time-Semantic-Segmentation
Swin-Transformer-Object-Detection - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
Swin-Transformer-Serve - Deploy Swin Transformer using TorchServe
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Video-Swin-Transformer - This is an official implementation for "Video Swin Transformers".
HRNet-Semantic-Segmentation - 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
PaddleClas - A treasure chest for visual classification and recognition powered by PaddlePaddle
semantic-segmentation-pytorch - Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset