I want to collect computer vision paper that has source code in github
Just for my fast-search & re-search. ^^
If you find what I missed or If you want to add, please, let me know.
An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem Thorsten Beier, Bj ̈orn Andres†Ullrich K ̈othe, Fred A. Hamprech [code1] [code2]
Top-down Neural Attention by Excitation Backprop Jianming Zhang, Zhe Lin, Jonathan Brandt, Xiaohui Shen, Stan Sclaroff [code]
Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang, David Balduzzi, Wen Li [code]
Identity Mappings in Deep Residual Networks Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun [code]
Deep Networks with Stochastic Depth Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Weinberger [code]
Heat Diffusion Long-Short Term Memory Learning for 3D Shape Analysis Fan Zhu, Jin Xie and Yi Fang [code]
LIFT: Learned Invariant Feature Transform Kwang Moo Yi, Eduard Trulls, Vincent Lepetit, and Pascal Fua [code]
Region-based semantic segmentationwith end-to-end training [code]
Projective Bundle Adjustment from Arbitrary Initialization Using the Variable Projection Method Je Hyeong Hong, Christopher Zach, Andrew Fitzgibbon, Roberto Cipolla [code]
Non-rigid 3D Shape Retrieval viaLarge Margin Nearest Neighbor Embedding Ioannis Chiotellis, Rudolph Triebel, Thomas Windheuser, and Daniel Cremers [code]
Is Faster R-CNN Doing Well for Pedestrian Detection? Liliang Zhang, Liang Lin, XiaodanLiang, KaimingHe [code]
Graph-Based Consistent Matching For Structure-From-Motion Tianwei Shen, Siyu Zhu, Tian Fang, Runze Zhang, Long Quan [code]
A Neural Approach to Blind Motion Deblurring Ayan Chakrabarti [code]
ATGV-Net: Accurate Depth Super-Resolution Gernot Riegler, Matthias R ̈uther, Horst Bischof [code]
Pixelwise View Selection for Unstructured Multi-View Stereo Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm[code]
Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation Golnaz Ghiasi, Charless C. Fowlkes [code]
Distractor-supported single target tracking in extremely cluttered scenes Jingjing Xiao, Linbo Qiao, Rustam Stolkin, Ales Leonardis [code]
View Synthesis by Appearance Flow Tinghui Zhou, Shubham Tulsiani, Weilub Sun,Jitendra Mlik, Alexei A. Efros [code]
A Unified Multi-scale Deep Convolutional Neural Networkfor Fast Object Detection Zhaowei Cai, Quanfu Fan, Rogerio Feris, Nuno Vasconcelos [code]
Seed, Expand and Constrain: Three Principlesfor Weakly-Supervised Image Segmentation Alexander Kolesnikov, Christoph H. Lampert [code]
Deep3D : Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks Junyuan Xie, Ross Girshik, Ali Farhadi [code]
Fast, Exact & Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs Siddhartha Chandra & Iasonas Kokkinos [code]
A Generalized Successive Shortest Path Solver for Tracking Dividing Targets Carsten Haubold, Janez Aleš, Steffen Wolf, Fred A. Hamprecht [code1] [code2]
Accurate and Linear Time Pose Estimationfrom Points and Lines Alexander Vakhitov, Jan Funke, Francesc Moreno-Noguer[code]
Temporal Segment Networks:Towards Good Practices for Deep Action Recognition Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, Luc Van Gool [code]
Deep Markov Random Field for Image Modeling Zhirong Wu, Dahua Lin, Xiaoou Tang [code]
Depth--aawareVideoMagnification Julian F. P. Kooij, Jan C. van Gemert [code]
Structured Matching for Phrase Localization Mingzhe Wang, Mahmoud Azab, Noriyuki Kojima, Rada Mihalcea, Jia Deng [code]
Scalable Metric Learning via Weighted Approximate Rank Component Analysis Cijo Jose, François, Fleuret [code]
Resonant Deformable Matching:Simultaneous Registration and Reconstruction John Corring, Anand Rangarajan [code]
Deep Learning 3D Shape Surfaces using Geometry Images Ayan Sinha, Jing Bai, Karthik Ramani [code]
Do We Really Need to Collect Millions of Faces for Effective Face Recognition? Iacopo Masi, Anh Tuan Tran, Tal Hassner, Jatuporn Toy Leksut, Gerard Medioni1 [code]
Using Fast Weights to Attend to the Recent Past [paper] [code]
Learning to learn by gradient descent by gradient descent [paper] [code]
R-FCN: Object Detection via Region-based Fully Convolutional Networks [paper] [code]
Fast and Provably Good Seedings for k-Means [paper] [code]
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences [paper] [code]
Generative Adversarial Imitation Learning [paper] [code]
Adversarial Multiclass Classification: A Risk Minimization Perspective [paper] [code]
Unsupervised Learning for Physical Interaction through Video Prediction [paper] [code]
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks [paper] [code]
Sequential Neural Models with Stochastic Layers [paper] [code]
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering [paper] [code]
Interpretable Distribution Features with Maximum Testing Power [paper] [code]
PVANet: Lightweight Deep Neural Networks for Real-time Object Detection [paper] [code]
Convolutional Neural Fabrics for Architecture Learning [paper] [code]
Binarized Neural Networks [paper] [Code]
Identity Mappings in Deep Residual Networks Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun [code]
Is Faster R-CNN Doing Well for Pedestrian Detection? Liliang Zhang, Liang Lin, XiaodanLiang, KaimingHe [code]
Do We Really Need to Collect Millions of Faces for Effective Face Recognition? Iacopo Masi, Anh Tuan Tran, Tal Hassner, Jatuporn Toy Leksut, Gerard Medioni1 [code]
A Unified Multi-scale Deep Convolutional Neural Networkfor Fast Object Detection Zhaowei Cai, Quanfu Fan, Rogerio Feris, Nuno Vasconcelos [code]
Using Fast Weights to Attend to the Recent Past [paper] [code]
Learning to learn by gradient descent by gradient descent [paper] [code]