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can you please make a code for these models? thanks in advance
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Hi Alex! Thanks a lot again for your excellent work again. I want to ask you several questions about the operation of the overall system.
(1) It seems like the whole system has these four blocks: p…
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I have successfully converted yolo tiny to ONNX. Using the .cfg file [https://github.com/WongKinYiu/ScaledYOLOv4/blob/yolov4-tiny/cfg/yolov4-tiny.cfg](url) and the export.py code here [https://github.…
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@jkjung-avt
Hi, could we work together on the problem of the reduced accuracy? I believe I have similar issues in my implementation and I do not use any onnx conversion whatsoever. I would like to g…
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Add multi-object tracker (dynamic array of single object trackers):
* SORT-tracker: `cv::KalmanFilter` + Hungarian algorithm https://en.wikipedia.org/wiki/Hungarian_algorithm and https://arxiv.org…
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Discussion: https://www.reddit.com/r/MachineLearning/comments/hu7lyt/p_yolov4tiny_speed_1770_fps_tensorrtbatch4/
Full structure: [structure of yolov4-tiny.cfg model](https://netron.app/?url=https:/…
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- https://arxiv.org/abs/2107.08430
- 2021
本報告では,YOLOシリーズに改良を加え,新たな高性能検出器YOLOXを開発しました。
YOLO検出器をアンカーフリーに変更するとともに,非結合型ヘッドや最先端のラベル割り当て戦略SimOTAなどの先進的な検出技術を導入し,大規模なモデルの範囲で最先端の結果を得ることができました。
YOLO-Nano(…
e4exp updated
3 years ago
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- https://arxiv.org/abs/2104.10419
- 2021
オブジェクト検出器を実用化するためには、効果的かつ効率的であることが不可欠です。
この2つの課題を解決するために、我々は既存の改良点を総合的に評価し、推論時間をほぼ変えずにPP-YOLOの性能を向上させました。
本論文では、一連の改良点を分析し、それらが最終的なモデルの性能に与える影響を、インクリメンタ…
e4exp updated
3 years ago
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EfficientDet: Scalable and Efficient Object Detection
* paper: https://arxiv.org/abs/1911.09070v1
> First, we propose a weighted bi-directional feature pyramid network (BiFPN), which allows ea…
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Hi,
Thank you for your work, it's great.
I'm working with a team of mine on YOLO too. We have published [a paper](https://arxiv.org/abs/2005.13243) where we show that YOLO includes two principal iss…