TensorMask: A Foundation for Dense Object Segmentation
一.摘要 1.基于滑动窗口的目标检测生成稠密，规则网格的bounding-box是很火热的 2.相比之下，现代的实例分割方法被后述的方法所主导，它首先检测对象边界框，然后裁剪和分割这些区域，如Mask R-CNN所推广的那样 3.object detection中有dense的方法（如yolo，ssd，retinanet），也有R-CNN这类two-stage的方法；然而在instance seg
相关文章
- 1. 论文阅读：TensorMask: A Foundation for Dense Object Segmentation
- 2. 【ICCV2019】TensorMask：A Foundation for Dense Object Segmentation
- 3. 神经网络 | TensorMask: A Foundation for Dense Object Segmentation（何凯明团队新作）
- 4. RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation
- 5. 《Dense Residual Network for Retinal Vessel Segmentation》
- 6. Summary - A Transductive Approach for Video Object Segmentation
- 7. 论文笔记_2010-BMVC-Joint optimization for object class segmentation and dense stereo reconstruction
- 8. Focal Loss for Dense Object Detection
- 9. RetinaNet：Focal Loss for Dense Object Detection
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相关文章
- 1. 论文阅读：TensorMask: A Foundation for Dense Object Segmentation
- 2. 【ICCV2019】TensorMask：A Foundation for Dense Object Segmentation
- 3. 神经网络 | TensorMask: A Foundation for Dense Object Segmentation（何凯明团队新作）
- 4. RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation
- 5. 《Dense Residual Network for Retinal Vessel Segmentation》
- 6. Summary - A Transductive Approach for Video Object Segmentation
- 7. 论文笔记_2010-BMVC-Joint optimization for object class segmentation and dense stereo reconstruction
- 8. Focal Loss for Dense Object Detection
- 9. RetinaNet：Focal Loss for Dense Object Detection
- 10. RetinaNet--Focal Loss for Dense Object Detection