We saw many posts on object detections and models in the last couple of weeks.
However, these projects always come with a list of research papers.
If we get important research papers in one place, that would be awesome.
Today I am going to show you important research papers on deep learning object detection.
It contains a list of papers, a performance table for each model from 2014 to 2019, and its challenge.
The GitHub repository updated up to Aug 2020 and the link Deep Learning Object Detection.
The research link contains PDF and Source Code, so if you are looking for your project for any object detection library to use in Autonomous, Image, or Video recognition, Video edition, Graphics, etc., then this is the place we need to check first.
Example:
- [R-CNN] Rich feature hierarchies for accurate object detection and semantic segmentation | [CVPR’ 14] |
[pdf][official code - caffe]
Performance table like below:
| Detector | VOC07 (mAP@IoU=0.5) | VOC12 (mAP@IoU=0.5) | COCO (mAP@IoU=0.5:0.95) | Published In |
|---|---|---|---|---|
| R-CNN | 58.5 | – | – | CVPR’14 |
| SPP-Net | 59.2 | – | – | ECCV’14 |
| MR-CNN | 78.2 (07+12) | 73.9 (07+12) | – | ICCV’15 |
We can see more researchers popped in and produced more research papers since 2018.
Dataset challenge papers on PASCAL VOC Object Detection Challenge, ILSVRC Object Detection Challenge, MS COCO Object Detection Challenge, and Open Images Object Detection Challenge.
Thanks to GitHub Developer Hoya for his contribution to getting most of the research papers in one place.
Further Reading
Posts on Artificial Intelligence, Deep Learning, Machine Learning, and Design Thinking articles:
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