Computer Vision Reading Group

Reading List

Object detection

1. Rich feature hierarchies for accurate object detection and semantic segmentation paper
2. Fast R-CNN paper
3. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks paper
4. [read]R-FCN: Object Detection via Region-based Fully Convolutional Networks paper
5. [read]Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks paper
6. Feature Pyramid Networks for Object Detection paper
7. [read] A-Fast-RCNN: Hard positive generation via adversary for object detection paper github
8. [read] Generative Adversarial Networks paper
9. [read] Attend Refine Repeat: Active Box Proposal Generation via In-Out Localization paper caffe
10. [read] Spatial Memory for Context Reasoning in Object Detection paper
11. Accurate Single Stage Detector Using Recurrent Rolling Convolution paper
12. ME R-CNN: Multi-Expert Region-based CNN for Object Detection paper
13. [read] Beyond Skip Connections: Top-Down Modulation for Object Detection paper
14. Improving Object Detection With One Line of Code paper
15. S-OHEM: Stratified Online Hard Example Mining for Object Detection paper
16. Adaptive Object Detection Using Adjacency and Zoom Prediction paper caffe
17. You Only Look Once: Unified, Real-Time Object Detection paper
18. YOLO9000: Better, Faster, Stronger paper
19. Deformable Convolutional Networks paper mxnet
20. Learning Detection with Diverse Proposals paper caffe
21. Feature Pyramid Networks for Object Detection paper
22. [read] RON: Reverse Connection with Objectness Prior Networks for Object Detection paper

Text detection

1. Detecting Text in Natural Image with Connectionist Text Proposal Network paper
2. EAST: An Efficient and Accurate Scene Text Detector paper

Semantic Image Segmentation

1. Fully Convolutional Networks for Semantic Segmentation paper caffe
2. Semantic Image Sementation with Deep Convolutional Nets and Fully Connected CRF paper
3. Conditional Random Fields as Recurrent Neural Networks paper caffe
4. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs paper pytorch
5. [read] Fully Convolutional Instance-aware Semantic Segmentation paper mxnet
6. Loss Max-Pooling for Semantic Image Segmentation paper
7. [read] Mask R-CNN paper tf

Recognition and Detection in 3D

1. 3D ShapeNets: A Deep Representation for Volumetric Shapes paper matlab
2. VoxNet: A 3D Convolutional Neural Network for Real-Time Object Recognition paper Lasagne

Visual Reasoning

1. Inferring and Executing Programs for Visual Reasoning paper pytorch

Human motion

1. Unsupervised Learning of Depth and Ego-Motion from Video paper github

CNN and its property

1. Group Invariant Scattering paper
2. Invariant Scattering Convolution Networks paper
3. Structured Receptive Fields in CNNs paper
4. Dynamic Filter Networks paper
5. Multiscale Hierarchical Convolutional Networks paper
6. Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors paper

Image classification

1. Deep Residual Learning for Image Recognition paper

Lightweight CNN

1. Towards lightweight convolutional neural networks for object detection paper