PaddleClas
Swin-Transformer-Semantic-Segmentation
PaddleClas | Swin-Transformer-Semantic-Segmentation | |
---|---|---|
2 | 1 | |
5,262 | 1,081 | |
0.7% | 0.0% | |
5.4 | 0.0 | |
7 days ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
PaddleClas
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Baidu AI Research Team Introduces ‘PP-ShiTu’: A Practical Lightweight Image Recognition System
Quick 5 Min Read | Paper | Github
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Baidu Research Introduces PP-LCNet: A Lightweight CPU Convolutional Neural Network With Better Accuracy And Performance
3 Min Quick Read | Paper| Github PaddleClas
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
What are some alternatives?
Swin-Transformer-Object-Detection - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Swin-Transformer-Tensorflow - Unofficial implementation of "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" (https://arxiv.org/abs/2103.14030)
efficientnet - Implementation of EfficientNet model. Keras and TensorFlow Keras.
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Video-Swin-Transformer - This is an official implementation for "Video Swin Transformers".
Swin-Transformer-Serve - Deploy Swin Transformer using TorchServe
DWPose - "Effective Whole-body Pose Estimation with Two-stages Distillation" (ICCV 2023, CV4Metaverse Workshop)
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
SeMask-Segmentation - [NIVT Workshop @ ICCV 2023] SeMask: Semantically Masked Transformers for Semantic Segmentation