[2019CVPR论文笔记]One-Shot Object Detection with Co-Attention and Co-Excitation

时间 2020-12-30

标签 CVPR2019 Few-shot Learning 繁體版

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One-Shot Object Detection with Co-Attention and Co-Excitation 摘要 1.概论介绍 2.相关工作 3.研究方法 3.1 Model 3.2 Non-local object proposals 3.3 Squeeze and co-excitation 3.4 Proposal ranking 4. 实验结果论文连接：https://a

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1. 论文笔记：Integrated Object Detection and Tracking with Tracklet-Conditioned Detection
2. 《EfficientDet：Scalable and Efficient Object Detection》论文笔记
3. 【论文笔记】：Object detection with location-aware deformable convolution and backward attention filtering
4. 论文笔记：Reinforcing LiDAR-Based 3D Object Detection with RGB and 3D Information
5. 论文笔记——Camouflaged Object Detection
6. 【论文笔记 detection】soft-nms: Improving Object Detection With One Line of Code
7. 【论文笔记】Object Contour Detection with a Fully Convolutional Encoder-Decoder Network
8. [Arxiv1706] Few-Example Object Detection with Model Communication 论文笔记
9. 【论文阅读笔记】Aspect-based sentiment analysis with alternating coattention networks
10. Bottom-up Object Detection by Grouping Extreme and Center Points 论文笔记

>>更多相关文章<<