Summaries and reviews of interesting deep learning papers.

2006:

• Reducing the dimensionality of data with neural networks - Review
  • G. E. Hinton and R. R. Salakhutdinov
  • Science

2012:

• ImageNet Classification with Deep Convolutional Neural Networks - Review
  • Alex Krizhevsky, Ilya Sutskever and Geoffrey E. Hinton
  • NIPS

2014:

• How transferable are features in deep neural networks? - Review
  • Jason Yosinski, Jeff Clune, Yoshua Bengio and Hod Lipson
  • NIPS

2015:

• Going Deeper with Convolutions - Review

  • Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke and Andrew Rabinovich
  • CVPR

• Very Deep Convolutional Networks for Large-Scale Image Recognition - Review

  • Karen Simonyan and Andrew Zisserman
  • ICLR

• Region-based Convolutional Networks for Accurate Object Detection and Segmentation - Review

  • Ross Girshick, Jeff Donahue, Trevor Darrell and Jitendra Malik
  • TPAMI

• Fast R-CNN - Review

  • Ross Girshick
  • ICCV

2016:

• Deep Residual Learning for Image Recognition - Review

  • Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun (Microsoft Research)
  • CVPR

• Scene Structure Inference through Scene Map Estimation - Review

  • Moos Hueting, Virica Patraucean, Maks Ovsjanikov and Niloy J. Mitra
  • VMV

• Interaction Networks for Learning about Objects, Relations and Physics - Review

  • Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Rezende and Koray Kavukcuoglu
  • NIPS

2017:

• Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution - Review

  • Wei-Shang Lai, Jia-Bin Huang, Narendra Ahuja and Ming-Hsuan Yang
  • CVPR

• Unsupervised Representation Learning by Sorting Sequences - Review

  • Hsin-Ying Lee, Jia-Bin Huang, Maneesh Singh and Ming-Hsuan Yang
  • ICCV

• Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics - Review

  • Alex Kendall, Yarin Gal and Roberto Cipolla
  • ArXiv preprint

• Decomposing Motion and Content for Natural Video Sequence Prediction - Review

  • Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin and Honglak Lee
  • ICLR

• Associative Domain Adaptation - Review

  • Philip Haeusser, Thomas Frerix, Alexander Mordvintsev and Daniel Cremers
  • ICCV

• Unsupervised Learning of Depth and Ego-Motion from Video - Review

  • Tinghui Zhou, Matthew Brown, Noah Snavely and David G. Lowe
  • CVPR

2018:

• DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNs - Review

  • Shi Yan, Chenglei Wu, Lizhen Wang, Feng Xu, Liang An, Kaiwen Guo and Yebin Liu
  • ECCV

• Deep Depth Completion of a Single RGB-D Image - Review

  • Yinda Zhang and Thomas Funkhouser
  • CVPR

--To Read--:

• Learning Category-Specific Mesh Reconstruction from Image Collections - Review

  • Angjoo Kanazawa, Shubham Tulsiani, Alexei A. Efros and Jitendra Malik
  • ECCV 2018

• Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks - Review

  • Adria Recasens, Petr Kellnhofer, Simon Stent, Wojciech Matusik, and Antonio Torralba
  • ECCV 2018

• Tracking Emerges by Colorizing Videos - Review

  • Carl Vondrick, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama and Kevin Murphy
  • ECCV 2018