CV-papers ( ᵔ ᴗ ᵔ )✌
Survey papers to follow in the Computer Vision area included object detection, image segmentation, object tracking, super resolution
object Detection
2019 Four object Detection Review Papers:
Imbalance Problems in Object Detection: A Review
- intro: under review at TPAMI
- arXiv
Recent Advances in Deep Learning for Object Detection
- intro: From 2013 (OverFeat) to 2019 (DetNAS)
- arXiv
A Survey of Deep Learning-based Object Detection
- intro: From Fast R-CNN to NAS-FPN
- arXiv
Object Detection in 20 Years: A Survey
- intro: This work has been submitted to the IEEE TPAMI for possible publication
- arXiv
More papers on object detection can be found at: github
Image segmentation
Deep Semantic Segmentation of Natural and Medical Images: A Review
- intro: From FCN (2014) to Auto-DeepLab (2019), this review contains 179 semantic segmentation and medical image segmentation references
- arXiv
Understanding Deep Learning Techniques for Image Segmentation
- intro: This review introduces more than 30 mainstream segmentation algorithms (including semantic / instance segmentation) from 2013 to 2019, more than 50 data sets, a total of 224 references
- arXiv
object Tracking
A Review of Visual Trackers and Analysis of its Application to Mobile Robot
- intro: This goal tracking review contains 185 references! From traditional methods to the latest deep learning networks
- arXiv
Deep Learning in Video Multi-Object Tracking: A Survey
- intro: 38-page overview of object tracking, including more than 30 mainstream algorithms, with a total of 174 references
- arXiv
Super resolution
A Deep Journey into Super-resolution: A survey
Deep Learning for Image Super-resolution: A Survey
Medical image segmentation
Deep learning for cardiac image segmentation: A review
- intro: This review of medical image segmentation from FCN (2014) to Dense U-net (2019), more than 250 references (the workload of light drawing in the paper is super large)
- arXiv
Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications
Saliency object detection
Salient Object Detection in the Deep Learning Era: An In-Depth Survey
Behavior recognition
Spatio-temporal Action Recognition: A Survey
Depth estimation
Monocular Depth Estimation: A Survey