✨RF-DETR: Neural Architecture Search for Real-Time Detection Transformers
📝 Summary:
RF-DETR is a light-weight detection transformer leveraging weight-sharing NAS to optimize accuracy-latency tradeoffs across diverse datasets. It significantly outperforms prior state-of-the-art, being the first real-time detector to surpass 60 AP on COCO.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09554
• PDF: https://arxiv.org/pdf/2511.09554
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✓ https://t.iss.one/DataScienceT
#ObjectDetection #ComputerVision #MachineLearning #NeuralArchitectureSearch #Transformers
📝 Summary:
RF-DETR is a light-weight detection transformer leveraging weight-sharing NAS to optimize accuracy-latency tradeoffs across diverse datasets. It significantly outperforms prior state-of-the-art, being the first real-time detector to surpass 60 AP on COCO.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09554
• PDF: https://arxiv.org/pdf/2511.09554
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#ObjectDetection #ComputerVision #MachineLearning #NeuralArchitectureSearch #Transformers