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【Bias 03】Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
時間 2021-06-10
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Related work Improving corruption robustness 去除腐蝕:(1)提出一種基於DNN,恢復雨霧圖片質量的方法。(2)預處理中去除雨。但這種方法都是針對某種腐蝕。 數據增強:把腐蝕數據加入訓練。(1)blurred images上分類器表現脆弱,通過在blurred images上fine-tune提高對它的魯棒性。(2)在一種腐蝕上fine-tune,並不能
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相關文章
1.
【數據增強】Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
2.
Pillar-based Object Detection for Autonomous Driving
3.
解讀ECCV2020:Pillar-based Object Detection for Autonomous Driving
4.
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5.
Stereo R-CNN based 3D Object Detection for Autonomous Driving
6.
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving Yurong
7.
每天一篇論文 373/1000 PSEUDO-LIDAR++:ACCURATE DEPTH FOR 3D OBJECT DETECTION IN AUTONOMOUS DRIVING
8.
論文閱讀CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
9.
[論文解讀]Multi-View 3D Object Detection Network for Autonomous Driving
10.
MV3D:Multi-View 3D Object Detection Network for Autonomous Driving(翻譯)
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