involution
efficientdet-pytorch
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involution | efficientdet-pytorch | |
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6 | 1 | |
1,306 | 1,550 | |
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0.0 | 4.1 | |
almost 3 years ago | 9 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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involution
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[R] Involution: Inverting the Inherence of Convolution for Visual Recognition
PDF Link | Landing Page | Read as web page on arXiv Vanity
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[P] PyTorch Involution layer wrapper
Have you benchmarked it against the official implementations? Would be interesting to see what the difference is versus their CUDA version.
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[D] Paper Explained - Involution: Inverting the Inherence of Convolution for Visual Recognition (Full Video Analysis)
Code: https://github.com/d-li14/involution
efficientdet-pytorch
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Bounding box annotations and object orientation
However, there are papers on oriented object detectors (see https://arxiv.org/pdf/1911.07732.pdf) for example. In that paper, they do achieve better results using oriented bounding boxes. If you want to go down that route, I would suggest using the EfficientDet model, because the PyTorch code that you'll find for it is quite easy to understand and modify. For example, I've taken https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch, and modified it to include a "thing-ness" logit, and this was pretty easy to do. Classic EfficientDet models only include logits (aka output neurons that get softmax-ed) for each class, and if any one of these class neurons is greater than 0.5, then it is considered "a thing". Anyway - that's digression, but my point is that I've thought about adding oriented box support to an EfficientDet model, and it didn't seem to be too hard, although I haven't actually done it. If I was to start now, I would probably go with https://github.com/rwightman/efficientdet-pytorch, since Ross Wightman's models are becoming a de-facto standard in the PyTorch world for all things image-related.
What are some alternatives?
mmdetection - OpenMMLab Detection Toolbox and Benchmark
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Im2Vec - [CVPR 2021 Oral] Im2Vec Synthesizing Vector Graphics without Vector Supervision
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
yolact_edge - The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.
Yet-Another-EfficientDet-Pytorch - The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
unilm - Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
manydepth - [CVPR 2021] Self-supervised depth estimation from short sequences
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
MPRNet - [CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.
ros-semantic-segmentation-pytorch - Pytorch implementation of Semantic Segmentation in ROS on MIT ADE20K dataset based on semantic-segmentation-pytorch by CSAIL