論文筆記：Large-Scale Object Detection in the Wild from Imbalanced Multi-Labels
這是中科院計算所的一篇討論大規模目標檢測的論文，主要解決多標籤，類別不均衡的問題。論文地址 在過去的幾年裏，目標檢測領域取得很大的進步。Pascal VOC、MS COCO等具有高質量標註的通用目標檢測數據集極大地推動了OD的發展。然而，這些數據集在今天看來是相當小的，並開始在一定程度上限制OD的發展。人們更多關注於數據集上的原子問題，而不是在更困難的場景中研究OD。 Open Image標註過程
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相關文章
- 1. 論文筆記：Domain Adaptive Faster R-CNN for Object Detection in the Wild
- 2. Domain adaptive faster-rcnn for object detection in the wild 論文筆記
- 3. Traffic-Sign Detection and Classification in the Wild 論文筆記
- 4. Material Recognition in the Wild with the Materials in Context Database論文筆記
- 5. 【論文筆記】Learning from Synthetic Data for Crowd Counting in the Wild
- 6. Borrow from Anywhere: Pseudo Multi-modal Object Detection in Thermal Imagery論文筆記
- 7. 1604.Person Re-identification in the Wild 論文筆記
- 8. 【論文筆記】Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
- 9. 【論文閱讀筆記】Towards Accurate Multi-person Pose Estimation in the Wild
- 10. 論文筆記——Camouflaged Object Detection