Li Mu's intensive reading paper: DETR End to End Object Detection with Transformers - Code World

Li Mu's intensive reading paper: DETR End to End Object Detection with Transformers

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Origin blog.csdn.net/iwill323/article/details/128450164

Li Mu's intensive reading paper: DETR End to End Object Detection with Transformers

End-to-End Object Detection with Transformers (DETR) paper reading and understanding

Paper reading notes 9-Deformable DETR: Deformable Transformers for end-to-end object detection

DETR：end-to-end object detection with transformers

Intensive reading of Li Mu's paper: BERT "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding"

Interpretation of the paper: End-to-End Object Detection with Transformers

DEFORMABLE DETR: DEFORMABLE TRANSFORMERS FOR END-TO-END OBJECT DETECTION - A deformable attention mechanism for end-to-end object detection

The most violent target detection algorithm in DETR history End-to-End Object Detection with Transformers

Image Detection - DETR: End-to-End Object Detection with Transformers (arXiv 2020)

Li Mu's intensive reading paper: Swin transformer: Hierarchical vision transformer using shifted windows

Intensive reading of Li Mu's paper: ResNet "Deep Residual Learning for Image Recognition" by Kaiming He

Li Mu's intensive reading paper: MAE "Masked Autoencoders Are Scalable Vision Learners"

DETR - the beginning of end-to-end object detection using Transformer

Li Mu의 집중 읽기 논문: DETR End to End Object Detection with Transformers

Anmerkungen zum Papier: DETR: End-to-End Object Detection with Transformers (von Li Mu und Zhu)

Бумага для интенсивного чтения Ли Му: DETR End to End Object Detection with Transformers

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