MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features阅读笔记
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features 论文研究： 论文解决了实例分割的问题，即同时解决对象检测和语义分割的任务。论文提出了一个名为MaskLab的模型，它可以产生三个输出：box检测，语义分割和方向预测。建立在Faster-RCNN对象检测器之
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相关文章
- 1. 【阅读笔记】《Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network》（JSIS-Net）
- 2. 【论文阅读笔记】Rich feature hierarchies for accurate object detection and semantic segmentation
- 3. DL-semantic segmentation/Classification+Localization/Object Detection/Instance Segmentation
- 4. Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation阅读笔记
- 5. 论文阅读：FCIS：Fully Convolutional Instance-aware Semantic Segmentation
- 6. 「Deep Learning」Note on MaskLab
- 7. RCNN：Rich feature hierarchies for accurate object detection and semantic segmentation
- 8. 极简笔记 Instance Segmentation Survey
- 9. semantic segmentation 和instance segmentation
- 10. Boundary-aware Instance Segmentation 阅读笔记