Swin-Transformer-Serve
Swin-Transformer-Object-Detection
| Swin-Transformer-Serve | Swin-Transformer-Object-Detection | |
|---|---|---|
| 1 | 4 | |
| 26 | 1,710 | |
| - | 0.1% | |
| 0.0 | 0.0 | |
| almost 3 years ago | about 1 year ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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Swin-Transformer-Serve
Swin-Transformer-Object-Detection
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Transfer Learning on Swin Transformer as a backbone for instance segmentation using MRCNN
I'm currently trying to transfer learn a set of custom classes of fish, for instance segmentation. I have found the official implementation of Swin Transformer as a backbone for instance segmentation using MRCNN: https://github.com/SwinTransformer/Swin-Transformer-Object-Detection.
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Advice on Masters project | Vision transformers
Hi, So my project is to do with object detection on trash in the wild on this fairly obscure dataset: http://tacodataset.org/ and I was thinking of applying vision transformers to it for feature extraction. I was thinking of taking the YOLOX implementation and swapping out the backbone with swin transformers and perform bunch of comparisons/experiments for the write up. Sort of like how they applied swin transformers to mask R-CNN here but I am struggling to understand where to begin.
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[P] I implemented DeepMind's "Perceiver" in PyTorch
Yes, have a look at this paper.
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[P] Code and pretrained models for Swin Transformer are released (SOTA models on COCO and ADE20K)
Object detection on COCO: https://github.com/SwinTransformer/Swin-Transformer-Object-Detection
What are some alternatives?
Swin-Transformer-Semantic-Segmentation - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
torchlambda - Lightweight tool to deploy PyTorch models to AWS Lambda
YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
merged_depth - Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
Video-Swin-Transformer - This is an official implementation for "Video Swin Transformers".
QualityScaler - QualityScaler - image/video deeplearning upscaling for any GPU
Swin-Transformer-Tensorflow - Unofficial implementation of "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" (https://arxiv.org/abs/2103.14030)
Perceiver - Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow
deepmind-perceiver - My implementation of DeepMind's Perceiver
PaddleClas - A treasure chest for visual classification and recognition powered by PaddlePaddle