機器學習、深度學習、計算機視覺、自然語言處理及應用案例——乾貨分享（持續更新……）
- 人臉檢測與識別的趨勢和分析
【paper】【GitHub】 - 【全域性/區域性一致影象補全】《Globally and Locally Consistent Image Completion》S Iizuka, E Simo-Serra, H Ishikawa (2017)
【paper】【GitHub】 - 【基於CNN的面部表情識別】《Convolutional Neural Networks for Facial Expression Recognition》S Alizadeh, A Fazel [Stanford University] (2017)
【paper】【GitHub】 - 計算機視覺識別簡史：從 AlexNet、ResNet 到 Mask RCNN
【paper】【GitHub】 - 【臉部識別與聚類】《Face Identification and Clustering》A Dhingra [The State University of New Jersey] (2017)
【paper】【GitHub】 - 【(TensorFlow)通用U-Net影象分割】’Tensorflow Unet - Generic U-Net Tensorflow implementation for image segmentation’ by Joel Akeret
【paper】【GitHub】 - 【深度學習介紹之文字影象生成】《How to Convert Text to Images - Intro to Deep Learning #16 - YouTube》by Siraj Raval
【paper】【GitHub】 - 【一個深度神經網路如何對自動駕駛做端到端的訓練】《Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car》M Bojarski, P Yeres, A Choromanska, K Choromanski, B Firner, L Jackel, U Muller [NVIDIA Corporation & New York University & Google Research]
(2017)
【paper】【GitHub】 - 【基於深度卷積網路的動態場景關節語義與運動分割】《Joint Semantic and Motion Segmentation for dynamic scenes using Deep Convolutional Networks》N Haque, N D Reddy, K. M Krishna [International Institute of Information Technology & Max Planck Institute For Intelligent Systems]
(2017)
【paper】【GitHub】 - 【高解析度影象的實時語義分割】《ICNet for Real-Time Semantic Segmentation on High-Resolution Images》H Zhao, X Qi, X Shen, J Shi, J Jia [The Chinese University of Hong Kong & SenseTime Group Limited] (2017)
【paper】【GitHub】【GitHub2】【video】 - 【深度學習應用到語義分割的綜述】《A Review on Deep Learning Techniques Applied to Semantic Segmentation》A Garcia-Garcia, S Orts-Escolano, S Oprea, V Villena-Martinez, J Garcia-Rodriguez [University of Alicante] (2017)
【paper】【GitHub】 - 【醫學影象的深度遷移學習的原理】《Understanding the Mechanisms of Deep Transfer Learning for Medical Images》H Ravishankar, P Sudhakar, R Venkataramani, S Thiruvenkadam, P Annangi, N Babu, V Vaidya [GE Global Research] (2017)
【paper】【GitHub】 - 【(Torch)基於迴圈一致對抗網路的非配對圖到圖翻譯】
【paper】【GitHub】 -
【深度網路光流估計的演化】《FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks》E Ilg, N Mayer, T Saikia, M Keuper, A Dosovitskiy, T Brox [University of Freiburg] (2016)
【paper】【GitHub】【video】 -
【基於p-RNN的目標例項標註】《Annotating Object Instances with a Polygon-RNN》L Castrejon, K Kundu, R Urtasun, S Fidler [University of Toronto] (2017)
【paper】【GitHub】 - 《Dataset Augmentation for Pose and Lighting Invariant Face Recognition》D Crispell, O Biris, N Crosswhite, J Byrne, J L. Mundy [Vision Systems, Inc & Systems and Technology Research] (2017)
【paper】【GitHub】 - 【人臉的分割、交換與感知】《On Face Segmentation, Face Swapping, and Face Perception》Y Nirkin, I Masi, A T Tran, T Hassner, G Medioni [The Open University of Israel & USC] (2017)
【paper】【GitHub】 - 【面向視訊運動估計的幾何感知神經網路SfM-Net】《SfM-Net: Learning of Structure and Motion from Video》S Vijayanarasimhan, S Ricco, C Schmid, R Sukthankar, K Fragkiadaki [Google & Indri & CMU] (2017)
【paper】【GitHub】 - 【基於深度自學習的弱監督目標定位】《Deep Self-Taught Learning for Weakly Supervised Object Localization》Z Jie, Y Wei, X Jin, J Feng, W Liu [Tencent AI Lab & National University of Singapore] (2017)
【paper】【GitHub】 - 【單個影象的手部關鍵點檢測】《Hand Keypoint Detection in Single Images using Multiview Bootstrapping》T Simon, H Joo, I Matthews, Y Sheikh [CMU] (2017)
【paper】【GitHub】 - 《Hierarchical 3D fully convolutional networks for multi-organ segmentation》H R. Roth, H Oda, Y Hayashi, M Oda, N Shimizu, M Fujiwara, K Misawa, K Mori [Nagoya University & Nagoya University Graduate School of Medicine & Aichi Cancer Center] (2017)
【paper】【GitHub】 -
《Towards Large-Pose Face Frontalization in the Wild》X Yin, X Yu, K Sohn, X Liu, M Chandraker [Michigan State University & NEC Laboratories America & University of California, San Diego] (2017)
【paper】【paper2】【GitHub】 -
【通過觀察目標運動遷移學習特徵】《Learning Features by Watching Objects Move》D Pathak, R Girshick, P Dollár, T Darrell, B Hariharan [Facebook AI Research & UC Berkeley] (2016)
【paper】【GitHub】 -
【面向深度學習訓練的視訊標記工具】’BeaverDam - Video annotation tool for deep learning training labels’ by Anting Shen
【paper】【GitHub】 -
【生成對抗網路(GAN)圖片編輯】《Photo Editing with Generative Adversarial Networks | Parallel Forall》by Greg Heinrich
【paper】【paper2】【GitHub】 -
解讀Keras在ImageNet中的應用：詳解5種主要的影象識別模型
【paper】【GitHub】 - 《Adversarial PoseNet: A Structure-aware Convolutional Network for Human Pose Estimation》Y Chen, C Shen, X Wei, L Liu, J Yang [Nanjing University of Science and Technology & The University of Adelaide & Nanjing University] (2017)
【paper】【GitHub】 - 【結構感知卷積網路的人體姿態估計】《Adversarial PoseNet: A Structure-aware Convolutional Network for Human Pose Estimation》Y Chen, C Shen, X Wei, L Liu, J Yang [Nanjing University of Science and Technology & The University of Adelaide & Nanjing University] (2017)
【paper】【GitHub】 - 【基於神經網路的魯棒多視角行人跟蹤】《Robust Multi-view Pedestrian Tracking Using Neural Networks》M Z Alom, T M. Taha [University of Dayton] (2017)
【paper】【GitHub】 -
【視訊密集事件描述】”Dense-Captioning Events in Videos”
【paper】【GitHub】【data】 -
【受Siraj Raval深度學習視訊啟發的每週深度學習實踐挑戰】’Deep-Learning Challenges - Codes for weekly challenges on Deep Learning by Siraj’ by Batchu Venkat Vishal
【paper】【GitHub】 -
《SLAM with Objects using a Nonparametric Pose Graph》B Mu, S Liu, L Paull, J Leonard, J How [MIT] (2017)
【paper】【GitHub】 -
【醫學影象分割中迭代估計的歸一化輸入】《Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation》M Drozdzal, G Chartrand, E Vorontsov, L D Jorio, A Tang, A Romero, Y Bengio, C Pal, S Kadoury [Universite de Montreal & Imagia Inc] (2017)
【paper】【GitHub】 - 《An Analysis of Action Recognition Datasets for Language and Vision Tasks》S Gella, F Keller [University of Edinburgh] (2017)
【paper】【GitHub】