This repository contains short summaries of some machine learning papers.
ARCHITECTURESATTENTIONSpatial Transformer Networks
LOSS FUNCTIONSRECOGNITIONWorking hard to know your neighbor’s margins: Local descriptor learning loss (thanks, alexobednikov)
FACE RECOGNITIONFACESNeural Aggregation Network for Video Face Recognition (thanks, alexobednikov)
- Critical Learning Periods in Deep Neural Networks
GANSELF-DRIVING CARSHigh-Resolution Image Synthesis and Semantic Manipulation with Conditional GANsSELF-DRIVING CARSComputer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art
SELF-DRIVING CARSSystematic Testing of Convolutional Neural Networks for Autonomous DrivingSELF-DRIVING CARSSEGMENTATIONFast Scene Understanding for Autonomous DrivingSELF-DRIVING CARSArguing Machines: Perception-Control System Redundancy and Edge Case Discovery in Real-World Autonomous DrivingSELF-DRIVING CARSGANREINFORCEMENTVirtual to Real Reinforcement Learning for Autonomous DrivingSELF-DRIVING CARSEnd to End Learning for Self-Driving Cars
- Snapshot Ensembles: Train 1, get M for free
- Image Crowd Counting Using Convolutional Neural Network and Markov Random Field
REINFORCEMENTRainbow: Combining Improvements in Deep Reinforcement LearningREINFORCEMENTLearning to Navigate in Complex EnvironmentsGANUnsupervised Image-to-Image Translation NetworksRNNDilated Recurrent Neural NetworksOBJECT DETECTIONTRACKINGDetect to Track and Track to DetectARCHITECTURESDilated Residual Networks
OBJECT DETECTIONFeature Pyramid Networks for Object DetectionOBJECT DETECTIONSSD: Single Shot MultiBox DetectorOBJECT DETECTIONEFFICIENT NETWORKSMobileNets: Efficient Convolutional Neural Networks for Mobile Vision ApplicationsOBJECT DETECTIONMask R-CNN
FACESMulti-view Face Detection Using Deep Convolutional Neural Networks (aka DDFD) (thanks, arnaldog12)
GANOn the Effects of Batch and Weight Normalization in Generative Adversarial NetworksGANBEGANGANStackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial NetworksACTIVATION FUNCTIONSSelf-Normalizing Neural NetworksGANWasserstein GAN (aka WGAN)
OBJECT DETECTIONYOLO9000: Better, Faster, Stronger (aka YOLOv2)OBJECT DETECTIONYou Only Look Once: Unified, Real-Time Object Detection (aka YOLO)OBJECT DETECTIONPVANET: Deep but Lightweight Neural Networks for Real-time Object Detection
OBJECT DETECTIONR-FCN: Object Detection via Region-based Fully Convolutional NetworksOBJECT DETECTIONFaster R-CNNOBJECT DETECTIONFast R-CNNOBJECT DETECTIONRich feature hierarchies for accurate object detection and semantic segmentation (aka R-CNN)PEDESTRIANSTen Years of Pedestrian Detection, What Have We Learned?NEURAL STYLEInstance Normalization: The Missing Ingredient for Fast Stylization
HUMAN POSE ESTIMATIONStacked Hourglass Networks for Human Pose EstimationFACESDeepFace: Closing the Gap to Human-Level Performance in Face VerificationTRANSLATIONCharacter-based Neural Machine Translation
HUMAN POSE ESTIMATIONConvolutional Pose MachinesFACESHyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender RecognitionFACESFace Attribute Prediction Using Off-the-Shelf CNN FeaturesFACESCMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection- Conditional Image Generation with PixelCNN Decoders
GANInfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial NetsGANImproved Techniques for Training GANs- Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
ARCHITECTURESFractalNet: Ultra-Deep Neural Networks without Residuals- PlaNet - Photo Geolocation with Convolutional Neural Networks
OPTIMIZERSAdam: A Method for Stochastic OptimizationGANRNNGenerating images with recurrent adversarial networksGANAdversarially Learned Inference
ARCHITECTURESResnet in Resnet: Generalizing Residual ArchitecturesAUTOENCODERSRank Ordered AutoencodersARCHITECTURESWide Residual NetworksARCHITECTURESIdentity Mappings in Deep Residual NetworksREGULARIZATIONSwapout: Learning an ensemble of deep architectures- Multi-Scale Context Aggregation by Dilated Convolutions
- Texture Synthesis Through Convolutional Neural Networks and Spectrum Constraints
- Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
NEURAL STYLESemantic Style Transfer and Turning Two-Bit Doodles into Fine Artwork- Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis
SUPERRESOLUTIONAccurate Image Super-Resolution Using Very Deep Convolutional NetworksHUMAN POSE ESTIMATIONJoint Training of a Convolutional Network and a Graphical Model for Human Pose EstimationREINFORCEMENTHierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic MotivationCOLORIZATIONLet there be Color
NEURAL STYLEArtistic Style Transfer for Videos
REINFORCEMENTPlaying Atari with Deep Reinforcement LearningGENERATIVEAttend, Infer, Repeat: Fast Scene Understanding with Generative ModelsARCHITECTURESEFFICIENT NETWORKSSqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model sizeACTIVATION FUNCTIONSNoisy Activation FunctionsOBJECT DETECTIONIMAGE TO TEXTDenseCap: Fully Convolutional Localization Networks for Dense Captioning
REGULARIZATIONDeep Networks with Stochastic Depth
GANDeep Generative Image Models using a Laplacian Pyramid of Adversarial NetworksGENERATIVERNNATTENTIONDRAW A Recurrent Neural Network for Image Generation- Generating Images with Perceptual Similarity Metrics based on Deep Networks
GENERATIVEGenerative Moment Matching NetworksGENERATIVERNNPixel Recurrent Neural NetworksGANUnsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
NEURAL STYLEA Neural Algorithm for Artistic StyleNORMALIZATIONREGULARIZATIONBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftARCHITECTURESDeep Residual Learning for Image RecognitionACTIVATION FUNCTIONSFast and Accurate Deep Networks Learning By Exponential Linear Units (ELUs)- Fractional Max-Pooling
GANGenerative Adversarial NetworksARCHITECTURESInception-v4, Inception-ResNet and the Impact of Residual Connections on LearningNORMALIZATIONWeight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks