2019年计算机视觉综述论文汇总

【导读】本文整理了2019年计算机视觉方面的综述论文，包含目标检测、图像分割(含语义/实例分割)、目标跟踪、医学图像分割、显著性目标检测、行为识别、深度估计等。可以使读者对相关

目标检测

2019 四大目标检测综述论文：

Imbalance Problems in Object Detection: A Review

intro: under review at TPAMI
链接：https://arxiv.org/abs/1909.00169

Recent Advances in Deep Learning for Object Detection

intro: From 2013 (OverFeat) to 2019 (DetNAS
链接：https://arxiv.org/abs/1908.03673

A Survey of Deep Learning-based Object Detection

intro：From Fast R-CNN to NAS-FPN
链接：https://arxiv.org/abs/1907.09408

Object Detection in 20 Years: A Survey

intro：This work has been submitted to the IEEE TPAMI for possible publication
链接：https://arxiv.org/abs/1905.05055

目标检测更多论文详见：【资源】最全目标检测论文汇总（含最新 2019）

图像分割

Deep Semantic Segmentation of Natural and Medical Images: A Review

intro: 从 FCN(2014) 到 Auto-DeepLab(2019)，本综述共含179篇语义分割和医学图像分割参考文献
链接: https://arxiv.org/abs/1910.07655Understanding

Deep Learning Techniques for Image Segmentation

intro: 本综述介绍了从2013年到2019年，主流的30多种分割算法（含语义/实例分割），50多种数据集，共计224篇参考文献
链接: https://arxiv.org/abs/1907.06119

目标跟踪

A Review of Visual Trackers and Analysis of its Application to Mobile Robot

intro: 本目标跟踪综述共含185篇参考文献！从传统方法到最新的深度学习网络
链接: https://arxiv.org/abs/1910.09761

Deep Learning in Video Multi-Object Tracking: A Survey

intro: 38页目标跟踪综述，含30多种主流算法，共计174篇参考文献
链接: https://arxiv.org/abs/1907.12740

超分辨率

A Deep Journey into Super-resolution: A survey
链接: https://arxiv.org/abs/1904.07523Deep
Learning for Image Super-resolution: A Survey

链接:https://arxiv.org/abs/1902.06068

医学图像分割

Deep learning for cardiac image segmentation: A review

intro: 本医学图像分割综述从FCN(2014)到Dense U-net(2019)，超过250篇的参考文献（论文中光画图的工作量就超级大）
链接: https://arxiv.org/abs/1911.03723

Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications

链接: https://arxiv.org/abs/1911.02521

自动驾驶

A Survey of Autonomous Driving: Common Practices and Emerging Technologies

intro: 在本次自动驾驶系统调查中，本文概述了一些关键创新以及现有系统。涉及内容如下： 1. 前景和挑战 2. 自动驾驶系统架构 3. 传感器 4. 定位和建图技术 5. 感知(2D/3D)：目标检测、跟踪、道路和车道线检测 6. 评估方法 7. 自动驾驶相关数据集 8. 自动驾驶开源工具
链接: https://arxiv.org/abs/1906.05113

显著性目标检测

Salient Object Detection in the Deep Learning Era: An In-Depth Survey

链接: https://arxiv.org/abs/1904.09146
github: https://github.com/wenguanwang/SODsurvey行为识别Spatio-temporal

Action Recognition: A Survey

链接: https://arxiv.org/abs/1901.09403

深度估计

Monocular Depth Estimation: A Survey

链接: https://arxiv.org/abs/1901.09402

来源：知乎
作者：Amusi