This repository contains short summaries of some machine learning papers.

• UNSUPERVISED LEARNING ECCV 2018 Deep Clustering for Unsupervised Learning of Visual Features
• OBJECT DETECTION POINT CLOUD SELF-DRIVING CARS ECCV 2018 Deep Continuous Fusion for Multi-Sensor 3D Object Detection
• AUDIO SOUND SOURCE LOCALIZATION ACTION RECOGNITION SOUND SOURCE SEPARATION SELF-SUPERVISED ECCV 2018 Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
• UNCERTAINTY ECCV 2018 Towards Realistic Predictors
• OBJECT DETECTION ECCV 2018 Acquisition of Localization Confidence for Accurate Object Detection
• OBJECT DETECTION ECCV 2018 CornerNet: Detecting Objects as Paired Keypoints
• NORMALIZATION ECCV 2018 Group Normalization
• ARCHITECTURES ATTENTION ECCV 2018 Convolutional Networks with Adaptive Inference Graphs

• ARCHITECTURES ATTENTION Spatial Transformer Networks (thanks, alexobednikov)

• LOSS FUNCTIONS RECOGNITION Working hard to know your neighbor’s margins: Local descriptor learning loss (thanks, alexobednikov)

• FACE RECOGNITION FACES Neural Aggregation Network for Video Face Recognition (thanks, alexobednikov)

• Critical Learning Periods in Deep Neural Networks
• GAN SELF-DRIVING CARS High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
• SELF-DRIVING CARS Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art

• GAN Progressive Growing of GANs for Improved Quality, Stability, and Variation

• SELF-DRIVING CARS Systematic Testing of Convolutional Neural Networks for Autonomous Driving
• SELF-DRIVING CARS SEGMENTATION Fast Scene Understanding for Autonomous Driving
• SELF-DRIVING CARS Arguing Machines: Perception-Control System Redundancy and Edge Case Discovery in Real-World Autonomous Driving
• SELF-DRIVING CARS GAN REINFORCEMENT Virtual to Real Reinforcement Learning for Autonomous Driving
• SELF-DRIVING CARS End 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
• REINFORCEMENT Rainbow: Combining Improvements in Deep Reinforcement Learning
• REINFORCEMENT Learning to Navigate in Complex Environments
• GAN Unsupervised Image-to-Image Translation Networks
• RNN Dilated Recurrent Neural Networks
• OBJECT DETECTION TRACKING Detect to Track and Track to Detect
• ARCHITECTURES Dilated Residual Networks

• OBJECT DETECTION Feature Pyramid Networks for Object Detection
• OBJECT DETECTION SSD: Single Shot MultiBox Detector
• OBJECT DETECTION EFFICIENT NETWORKS MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
• OBJECT DETECTION Mask R-CNN

• FACES Multi-view Face Detection Using Deep Convolutional Neural Networks (aka DDFD) (thanks, arnaldog12)

• GAN On the Effects of Batch and Weight Normalization in Generative Adversarial Networks
• GAN BEGAN
• GAN StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
• ACTIVATION FUNCTIONS Self-Normalizing Neural Networks
• GAN Wasserstein GAN (aka WGAN)

• OBJECT DETECTION YOLO9000: Better, Faster, Stronger (aka YOLOv2)
• OBJECT DETECTION You Only Look Once: Unified, Real-Time Object Detection (aka YOLO)
• OBJECT DETECTION PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection

• OBJECT DETECTION R-FCN: Object Detection via Region-based Fully Convolutional Networks
• OBJECT DETECTION Faster R-CNN
• OBJECT DETECTION Fast R-CNN
• OBJECT DETECTION Rich feature hierarchies for accurate object detection and semantic segmentation (aka R-CNN)
• PEDESTRIANS Ten Years of Pedestrian Detection, What Have We Learned?
• NEURAL STYLE Instance Normalization: The Missing Ingredient for Fast Stylization

• HUMAN POSE ESTIMATION Stacked Hourglass Networks for Human Pose Estimation
• FACES DeepFace: Closing the Gap to Human-Level Performance in Face Verification
• TRANSLATION Character-based Neural Machine Translation

• HUMAN POSE ESTIMATION Convolutional Pose Machines
• FACES HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
• FACES Face Attribute Prediction Using Off-the-Shelf CNN Features
• FACES CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection
• Conditional Image Generation with PixelCNN Decoders
• GAN InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
• GAN Improved Techniques for Training GANs
• Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

• ARCHITECTURES FractalNet: Ultra-Deep Neural Networks without Residuals
• PlaNet - Photo Geolocation with Convolutional Neural Networks
• OPTIMIZERS Adam: A Method for Stochastic Optimization
• GAN RNN Generating images with recurrent adversarial networks
• GAN Adversarially Learned Inference

• ARCHITECTURES Resnet in Resnet: Generalizing Residual Architectures
• AUTOENCODERS Rank Ordered Autoencoders
• ARCHITECTURES Wide Residual Networks
• ARCHITECTURES Identity Mappings in Deep Residual Networks
• REGULARIZATION Swapout: 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 STYLE Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artwork
• Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis
• SUPERRESOLUTION Accurate Image Super-Resolution Using Very Deep Convolutional Networks
• HUMAN POSE ESTIMATION Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
• REINFORCEMENT Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
• COLORIZATION Let there be Color

• NEURAL STYLE Artistic Style Transfer for Videos

• REINFORCEMENT Playing Atari with Deep Reinforcement Learning
• GENERATIVE Attend, Infer, Repeat: Fast Scene Understanding with Generative Models
• ARCHITECTURES EFFICIENT NETWORKS SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
• ACTIVATION FUNCTIONS Noisy Activation Functions
• OBJECT DETECTION IMAGE TO TEXT DenseCap: Fully Convolutional Localization Networks for Dense Captioning

• REGULARIZATION Deep Networks with Stochastic Depth

• GAN Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
• GENERATIVE RNN ATTENTION DRAW A Recurrent Neural Network for Image Generation
• Generating Images with Perceptual Similarity Metrics based on Deep Networks
• GENERATIVE Generative Moment Matching Networks
• GENERATIVE RNN Pixel Recurrent Neural Networks
• GAN Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

• NEURAL STYLE A Neural Algorithm for Artistic Style
• NORMALIZATION REGULARIZATION Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
• ARCHITECTURES Deep Residual Learning for Image Recognition
• ACTIVATION FUNCTIONS Fast and Accurate Deep Networks Learning By Exponential Linear Units (ELUs)
• Fractional Max-Pooling
• GAN Generative Adversarial Networks
• ARCHITECTURES Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
• NORMALIZATION Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks