Paper-Summary

A Summary and notes about the papers I have read.

Deep Image Compression Relevant Papers:

• 1511.06085 Variable Rate Image Compression with Recurrent Neural Networks

• 1611.01704 End-to-end Optimized Image Compression

• 1608.05148 Full Resolution Image Compression with Recurrent Neural Networks*

• 1703.00395 Lossy Image Compression with Compressive Autoencoders (Twitter,CAE)

• 1705.05823 Real-Time Adaptive Image Compression (WaveOne,ICML)

• 1709.08855 Learning to Inpaint for Image Compression

• 1801.04260 Conditional Probability Models for Deep Image Compression (ETHZ)

• 1801.09392 Shift-Net: Image Inpainting via Deep Feature Rearrangement (Zy Yan)

• 1803.03004 Learning Effective Binary Visual Representations with Deep Networks (Wu Jianxin)

• 1804.04593 Deformation Aware Image Compression

• Towards_Image_Understanding_from_Deep_Compression_without_Decoding

• TrimmedCNN (Li Mu)

• 1804.06919 Video Compression through Image Interpolation*

Object Detection Relevant Papers:

Two-stage:

R-CNN series:

• 1311.2524 Rich feature hierarchies for accurate object detection and semantic segmentation [R-CNN]

• 1406.4729 Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition [SPPNet]

• 1504.08083 Fast R-CNN

• 1506.01497 Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

One-stage:

YOLO series:

• 1506.02640 You Only Look Once: Unified, Real-Time Object Detection [v1]

• 1612.08242 YOLO9000: Better, Faster, Stronger [v2]