IAST-ECCV2020
DA-Faster-RCNN
| IAST-ECCV2020 | DA-Faster-RCNN | |
|---|---|---|
| 1 | 1 | |
| 84 | 47 | |
| - | - | |
| 1.8 | 5.4 | |
| over 2 years ago | 8 months ago | |
| Python | Python | |
| - | MIT License |
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IAST-ECCV2020
DA-Faster-RCNN
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[R] DA-Faster RCNN
I have reimplemented DA-Faster RCNN using Detectron2 one of the most important architecture for domain adaptation for object detection. This implementations is easy to use and can be used also with google colab :) here there is the link: https://github.com/GiovanniPasq/DA-Faster-RCNN
What are some alternatives?
Real-time-Semantic-Segmentation
DA-RetinaNet - Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'
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
globox - A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.
mmdetection - OpenMMLab Detection Toolbox and Benchmark
AdaTime - [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data
Transfer-Learning-Library - Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization