论文阅读《EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection》
------------------------背景分析--------------------------------------------- 立体匹配的难点： 无纹理区域、细节结构、小物体和邻近边界找到正确的对应关系 之前的立体网络存在的缺点： 1 对所有潜在视差的多个前向计算通路的计算负担 2 有限的感受野和缺乏上下文信息来推断不适定区域的相关性 3 大量由经验手动设计参数的后处理模块
相关文章
- 1. 论文阅读《Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching》
- 2. 论文阅读笔记《Pyramid Stereo Matching Network》
- 3. 论文阅读《Pyramid Stereo Matching Network》
- 4. 论文阅读《Edge Detection Using Convolutional Neural Network》
- 5. 论文《Matching Networks for One Shot Learning》阅读
- 6. 论文阅读：EfficientDet: Scalable and Efficient Object Detection
- 7. 论文阅读笔记《Cascade Residual Learning A Two-stage Convolutional Neural Network for Stereo Matching》
- 8. 论文阅读--Reinforced Cross-Modal Matching and Self-Supervised Imatation Learning for VLN Navigation
- 9. Richer Convolutional Features for Edge Detection 论文阅读
- 10. 论文研读：2016 DeMoN Depth and Motion Network for Learning Monocular Stereo
- 更多相关文章...
- • RSS 阅读器 - RSS 教程
- • C# 文本文件的读写 - C#教程
- • RxJava操作符（七）Conditional and Boolean
- • JDK13 GA发布：5大特性解读
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. 论文阅读《Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching》
- 2. 论文阅读笔记《Pyramid Stereo Matching Network》
- 3. 论文阅读《Pyramid Stereo Matching Network》
- 4. 论文阅读《Edge Detection Using Convolutional Neural Network》
- 5. 论文《Matching Networks for One Shot Learning》阅读
- 6. 论文阅读：EfficientDet: Scalable and Efficient Object Detection
- 7. 论文阅读笔记《Cascade Residual Learning A Two-stage Convolutional Neural Network for Stereo Matching》
- 8. 论文阅读--Reinforced Cross-Modal Matching and Self-Supervised Imatation Learning for VLN Navigation
- 9. Richer Convolutional Features for Edge Detection 论文阅读
- 10. 论文研读：2016 DeMoN Depth and Motion Network for Learning Monocular Stereo