Posts

Escaping the Big Data Paradigm with Compact Transformers

ComTriplet: Deep Clustering via CenterOriented Margin FreeTriplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets

SelfSupervised MultiModal Versatile Networks

Sparse MultiChannel Variational Autoencoder for the Joint Analysis of Heterogeneous Data

Scanner invariant representations for diffusion MRI harmonization

Contextaware virtual adversarial training for anatomicallyplausible segmentation

Datadriven discovery of coordinates and governing equations

From Variational to Deterministic Autoencoders

Emerging Properties in SelfSupervised Vision Transformers

The DiffusionSimulated Connectivity (DiSCo) Challenge

AAVAE: AugmentationAugmented Variational Autoencoders

Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation

Perceiver: General Perception with Iterative Attention

Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

Simple and Effective VAE Training with Calibrated Decoders

Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Uncertainty Estimation Review

Unadversarial examples: designing objects for robust vision

Conservative QLearning for Offline Reinforcement Learning

A generative modeling approach for interpreting populationlevel variability in brain structure

Dataset distillation

CLIP : Learning Transferable Visual Models From Natural Language Supervision

Distributional Reinforcement Learning with Quantile Regression

Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation

Intriguing properties of neural networks

Evasion attacks against machine learning at test time

Self supervised learning

FODNet: A Deep Learning Method for Fiber Orientation Distribution Angular Super Resolution

A Distributional Perspective on Reinforcement Learning

Similarity of Neural Network Representations Revisited

MedAL: Accurate and Robust Deep Active Learning for Medical Image Analysis

Fader Networks: Manipulating Images by Sliding Attributes

Attributebased regularization of latent spaces for variational autoencoders

AlphaGo/AlphaGoZero/AlphaZero/MuZero: Mastering games using progressively fewer priors

Domain Generalization via ModelAgnostic Learning of Semantic Features

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

ACVAE: Learning Semantic Representation with VAE for Adaptive Clustering

A Deep Neural Network's Loss Surface Contains Every Lowdimensional Pattern

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Diva: Domain invariant variational autoencoders

Phasic Policy Gradient

GSGD: Optimizing ReLU neural networks in its positively scaleinvariant space

PathSGD: PathNormalized Optimization in Deep Neural Networks

Munchausen Reinforcement Learning

Disentangled Representation Learning in Cardiac Image Analysis

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Temporal Consistency Objectives Regularize the Learning of Disentangled Representations

Isolating Sources of Disentanglement in VAEs

Disentangling by Factorising

Using Generative Models for Pediatric wbMRI

DynamicsAware Unsupervised Discovery of Skills

OnceCycleLR: SuperConvergence: Very Fast Training of NeuralNetworks Using Large Learning Rates

SelfAttention Generative Adversarial Networks

Accelerating Online Reinforcement Learning with Offline Datasets

A machine learningbased method for estimating the number and orientations of major fascicles in diffusionweighted magnetic resonance imaging

What Matters In OnPolicy Reinforcement Learning? A LargeScale Empirical Study

Deep Learning: A philosophical introduction

Featurerobustness, flatness and generalization error for deep neural networks

Sharp Minima can Generalize for Deep Nets

Agent57: Outperforming the human Atari benchmark

Demystifying Parallel and Distributed Deep Learning

Neuro4Neuro: A neural network approach for neural tract segmentation using largescale populationbased diffusion imaging

Never Give Up: Learning Directed Exploration Strategies

An exponential learning rate schedule for deep learning

Visualizing the Loss Landscape of Neural Nets

BEAR (Bootstrapping Error Accumulation Reduction)

Superfast Diffusion Tensor Imaging and Fiber Tractography Using Deep Learning

Classifyber, a robust streamlinebased linear classifier for white matter bundle segmentation

Representational drift in Recurrent Reinforcement Learning

Learning Latent Subspaces in Variational Autoencoders

L2 Regularization versus Batch and Weight Normalization

PHiSeg  Capturing Uncertainty in Medical Image Segmentation

Learning Macroscopic Brain Connectomes via GroupSparse Factorization

Implementation Matters in Deep RL: A Case Study on PPO and TRPO

UpsideDown ReinforcementLearning

Rigging the Lottery: Making All Tickets Winners

Deep learning reveals untapped information for local whitematter fiber reconstruction in diffusionweighted MRI

SPECTRAL GRAPH TRANSFORMER NETWORKS FOR BRAIN SURFACE PARCELLATION

Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

Single Headed Attention RNN: Stop Thinking With Your Head

Associative Compression Networks for Representation Learning

Stealing Machine Learning Models via Prediction APIs

Entrack: A DataDriven MaximumEntropy Approach to Fiber Tractography

Estimating localized complexity of whitematter wiring with GANs

MetaLearning Deep EnergyBased Memory Models

ETNet  Error Transition Network for Arbitrary Style Transfer

Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

Manifold mixup: Encouraging meaningful onmanifold interpolation as a regularizer

Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors

ipAMedGAN: INPAINTING OF ARBITRARILY REGIONS IN MEDICAL MODALITIES

On the Utility of Learning about Humans for HumanAI Coordination

Straight to the point: reinforcement learning for user guidance in ultrasound

PickandLearn: Automatic Quality Evaluation for NoisyLabeled Image Segmentation

Learning shape priors for robust cardiac MR segmentation from multiview images

Multistage prediction networks for data harmonization

Lookahead Optimizer: k steps forward, 1 step back

AdvantageWeighted Regression: Simple and Scalable OffPolicy Reinforcement Learning

On Boosting Semantic Street Scene Segmentation with Weak Supervision

Neural Discrete Representation Learning

Contextencoding Variational Autoencoder for Unsupervised Anomaly Detection

Reconciling modern machine learning practice and the biasvariance tradeoff

Emergent Tool Use from MultiAgent Interaction

StateRegularized Recurrent Neural Networks

Synergistic Image and Feature Adaptation Towards CrossModality Domain Adaptation for Medical Image Segmentation

StateReification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations

Reproducible White Matter Tract Segmentation Using 3D UNet on a Largescale DTI Dataset

Anatomical Priors for Image Segmentation via PostProcessing with Denoising Autoencoders

A Generalized Framework for Population Based Training

Evaluating the Search Phase of Neural Architecture Search

Don't Worry About the Weather Unsupervised ConditionDependent Domain Adaptation

Compound–protein interaction prediction with endtoend learning of neural networks for graphs and sequences

Cortical Surface Parcellation using Spherical Convolutional Neural Networks

EndtoEnd MultiTask Learning with Attention

dSNE: Domain Adaptation Using Stochastic Neighborhood Embedding

Superhuman AI for multiplayer poker

Iterative Projection and Matching

Attention Branch Network: Learning of Attention Mechanism for Visual Explanation

Striving for Simplicity in Offpolicy Deep Reinforcement Learning

GraphBased Global Reasoning Networks

Deep Active Learning for AxonMyelin Segmentation on Histology Data

HardnessAware Deep Metric Learning

CrDoCo PixelLevel Domain Transfer With CrossDomain Consistency

Why ReLU Networks Yield HighConfidence Predictions Far Away From the Training Data and How to Mitigate the Problem

Unsupervised Detection of White Matter Fiber Bundles with Stochastic Neural Networks

Towards Universal Object Detection by Domain Attention

Reinforced CrossModal Matching and SelfSupervised Imitation Learning for VisionLanguage Navigation

Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression

Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks

Learning Loss for Active Learning

Continuous Dice Coefficient: a Method for Evaluating Probabilistic Segmentations

Combined tract segmentation and orientation mapping for bundlespecific tractography

Residual Policy Learning

A General and Adaptive Robust Loss Function

DeepBundle: Fiber Bundle Parcellation with Graph Convolution Neural Networks

Multibranch Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation

Batch Policy Gradient Methods for Improving Neural Conversation Models

Embedded hyperparameter tuning by Simulated Annealing

qSpace Novelty Detection with Variational Autoencoders

Pretraining Deep ActorCritic Reinforcement Learning Algorithms With Expert Demonstrations

Multisource and Multitemporal Data Fusion in Remote Sensing

Speech2Face: Learning the Face Behind a Voice

Synthesized b0 for diffusion distortion correction (Synb0DisCo)

[sketchRNN] A Neural Representation of Sketch Drawings

The power of ensembles for active learning in image classification

Generative Adversarial Imitation Learning

Adversarial Examples Are Not Bugs, They Are Features

A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

DeepAtlas: Joint SemiSupervised Learning of Image Registration and Segmentation

[Contrastive Loss] Dimensionality Reduction by Learning an Invariant Mapping

Clipped Proximal Policy Optimization Algorithm

Learning Structured Output Representation using Deep Conditional Generative Models

Open Questions about Generative Adversarial Networks

ENet: A Deep Neural Network Architecture for RealTime Semantic Segmentation

Missing MRI Pulse Sequence Synthesis using MultiModal Generative Adversarial Network

GeoSay: A Geometric Saliency for Extracting Buildings in Remote Sensing Images

Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations

Deep Learning with Compute Canada

Active learning tutorials

Exploring Randomly Wired Neural Networks for Image Recognition

Learning how to Active Learn: A Deep Reinforcement Learning Approach

3D Whole Brain Segmentation using Spatially Localized Atlas Network Tiles

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

Semantic Image Synthesis with SpatiallyAdaptive Normalization

Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets

Unsupervised Domain Adaptation using FeatureWhitening and Consensus Loss

Data augmentation using learned transforms for oneshot medical image segmentation

Prototypical Networks for Fewshot Learning

Reverse Curriculum Generation for Reinforcement Learning

PlaNet: Learning Latent Dynamics for Planning from Pixels

Cotrained convolutional neural networks for automated detection of prostate cancer in multiparametric MRI

Adversarial Autoencoders

Novel deep learningbased method for prostate segmentation in T2weighted magnetic resonance imaging

Crossscanner and crossprotocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI

Spherical Harmonic Residual Network for Diffusion Signal Harmonization

An (almost) instant brain atlas segmentation for largescale studies

Diversity in Faces

Characterlevel Convolutional Networks for Text Classification

Deep MultiStructural Shape Analysis: Application to Neuroanatomy

Learning multiple visual domains with residual adapters

Harmonizing Diffusion MRI Data Across Multiple Sites and Scanners

Fully Convolutional Network with MultiStep Reinforcement Learning for Image Processing

A StyleBased Generator Architecture for Generative Adversarial Networks

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

hdetach: Modifying the LSTM Gradient Towards Better Optimization

Adaptive Fusion for RGBD Salient Object Detection

Combined Reinforcement Learning via Abstract Representations

DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Improved Image Captioning via Policy Gradient optimization of SPIDEr

ACN: Associative Compression Networks for Representation Learning

Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects

MetropolisHastings Generative Adversarial Networks

GoExplore

NAG: Network for Adversary Generation

NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines

Unsupervised brain lesion segmentation from MRI using a convolutional autoencoder

Memory Replay GANs

The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

From Recognition to Cognition: Visual Commonsense Reasoning

Structured Pruning of Neural Networks with BudgetAware Regularization

OBELISK – One Kernel to Solve Nearly Everything: Unified 3D Binary Convolutions for Image Analysis

Label Refinement Network for CoarsetoFine Semantic Segmentation

Learning to reinforcement learn

LowShot Learning from Imaginary Data

Automatically Designing CNN Architectures for Medical Image Segmentation

Learning Implicit Brain MRI Manifolds with Deep Learning

Incremental Learning for Semantic Segmentation of LargeScale Remote Sensing Data

SDRL: Interpretable and Dataefficient Deep Reinforcement Learning Leveraging Symbolic Planning

Mapping connectomes with diffusion MRI: deterministic or probabilistic tractography?

UNetVAE: A Probabilistic UNet for Segmentation of Ambiguous Images

Privacypreserving generative deep neural networks support clinical data sharing

Episodic curiosity through reachability

Cascaded Transforming Multitask Networks For Abdominal Biometric Estimation from Ultrasound

SeedNet: Automatic Seed Generation with Deep Reinforcement Learning for Robust Interactive Segmentation

Progressive Weight Pruning of DNNs using ADMM

Domain Adaptive Segmentation in Volume Electron Microscopy Imaging

Recurrent SqueezeandExcitation Context Aggregation Net for Single Image Deraining

Visual semantic navigation using scene priors

HeMIS: HeteroModal Image Segmentation

Residual Connections Encourage Iterative Inference

CBAM: Convolutional Block Attention Module

A Few Useful Things to Know about Machine Learning

Exploiting Semantics in Adversarial Training for ImageLevel Domain Adaptation

Rethinking the Value of Network Pruning

Deep Extreme Cut: From Extreme Points to Object Segmentation

DivideandConquer Reinforcement Learning

Tversky loss function for image segmentation using 3D fully convolutional deep networks

Superresolution of Sentinel2 images: Learning a globally applicable deep neural network

PixelSNAIL: An Improved Autoregressive Generative Model

TreeSegNet: Adaptive Tree CNNs for Subdecimeter Aerial Image Segmentation

Binarized Neural Networks

Batch normalization sampling

Learning Discriminators as Energy Networks in Adversarial Learning

Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets for IsoIntense Infant Brain MRI Segmentation

Predicting Parameters in Deep Learning

Large Scale GAN Training for High Fidelity Natural Image Synthesis

Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation

Feature Selective Networks for Object Detection

The Elephant in the Room

Towards the first adversarially robust neural network model on MNIST

Kronecker Recurrent Units

CLIPQ: Deep Network Compression Learning by InParallel PruningQuantization

Taking A Closer Look at Domain Shift: Categorylevel Adversaries for Semantics Consistent Domain Adaptation

Automatic 3D biventricular segmentation of cardiac images by a shapeconstrained multitask deep learning approach

PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis

MultiModal Convolutional Neural Network for Brain Tumor Segmentation

Style Augmentation: Data Augmentation via Style Randomization

On Multiplicative Integration with Recurrent Neural Networks

MorphNet: Fast & Simple ResourceConstrained Structure Learning of Deep Networks

Dual Attention Network for Scene Segmentation

DSSLIC: Deep Semantic Segmentationbased Layered Image Compression

TRAFIC: Fiber Tract Classification Using Deep Learning

All You Need is Love: Evading Hatespeech Detection

Learning Shape Priors for SingleView 3D Completion and Reconstruction

Datadriven Fiber Tractography With Neural Networks

What do Deep Networks Like to See?

Attentive Generative Adversarial Network for Raindrop Removal from A Single Image

Efficient Interactive Annotation of Segmentation Datasets with PolygonRNN++

BlockDrop: Dynamic Inference Paths in Residual Networks

CNN with Alternately Updated Clique

Functional Map of the World

Neural Processes

Learning a Discriminative Feature Network for Semantic Segmentation

HAMLET: Hierarchical Harmonic Filters for Learning Tracts from Diffusion MRI

Learning a Spatial Activation Function Restoration

Learning to Segment Every Thing

Scale equivariance in CNNs with vector fields

Mining on Manifolds: Metric Learning without Labels

Adaptive Neural Trees

Rethinking the Faster RCNN Architecture for Temporal Action Localization

Rotation Equivariant CNNs

Lightweight Probabilistic Deep Networks

MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features

Learning Transferable Deep Models for LandUse Classification with HighResolution Remote Sensing Images

Pose estimation with a Riemannian Geometry loss

“LearningCompression” Algorithms for Neural Net Pruning

Cascade RCNN: Delving into High Quality Object Detection

Autofocus layer

SqueezeandExcitation Networks (2017 ImageNet winner)

Deep Layer Aggregation

Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation

TensorTrain Recurrent Neural Networks for Video Classification

Burst Denoising with Kernel Prediction Networks

ClusterNet: Detecting Small Objects in Large Scenes by Exploiting SpatioTemporal Information

Star shape Prior

Normalized Cut Loss for Weaklysupervised CNN Segmentation

Guide Me: Interacting with Deep Networks

Deep Networks With Shape Priors for Nucleus Detection

Domain Shift for Semantic Segmentation

Learning Longerterm Dependencies in RNNs with Auxiliary Losses

EnhanceNet : Classification Driven Dynamic Image Enhancement

Ship wakedetection procedure using conjugate gradient trained artificial neural networks

The Method of Auxiliary Coordinates

Beyond the PixelWise Loss for TopologyAware Delineation

Simple Does It: Weakly Supervised Instance and Semantic Segmentation

Budgeted Super Networks

DOTA: A Largescale Dataset for Object Detection in Aerial Images

Siamese LSTMbased fiber structural similarity network (FS2NET) for rotation invariant brain tractography segmentation

Anatomical Priors for Unsupervised Biomedical Segmentation

Interactive Image Segmentation with Latent Diversity

Adversarial Structure Matching Loss for Image Segmentation

Knowledge Distillation by OntheFly Native Ensemble

Dense labeling of large remote sensing imagery with convolutional neural networks: a simple and faster alternative to stitching output label maps

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Automatic Cardiac Disease Assessment on cineMRI via TimeSeries Segmentation and Domain Specific Features

Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps

Indoor Scene Labeling

Densely Connected Bidirectional LSTM

Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation

Monotonic Chunkwise Attention

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Revisiting Dilated Convolution: A Simple Approach for Weakly and Semi Supervised Semantic Segmentation

The Lottery Ticket Hypothesis: Training Pruned Neural Network Architectures

MEnet: A Metric Expression Network for Salient Object Segmentation

The Intrinsic Dimension of Objective Landscapes

Deep Complex Networks

Select, Attend, and Transfer: Light, Learnable Skip Connections

Adaptive Costsensitive Online Classification

An AnchorFree Region Proposal Network for Faster RCNN based Text Detection Approaches

Survey: Network compression and speedup

MultiStage MultiTask Neural Network for Aerial Scene Interpretation and Geolocalization

Locally Adaptive Learning Loss for Semantic Image Segmentation

Betweenclass Learning for Image Classification

Learning Sparse Structured Ensembles with SGMCMC and Network Pruning

GMMBased Synthetic Samples for Classification of Hyperspectral Images With Limited Training Data

On Characterizing the Capacity of Neural Networks Using Algebraic Topology

Optimal Transport for Deep Joint Transfer Learning

Bayesian Methods for Machine Learning

On the importance of single directions for generalization

RetinaNet: Focal Loss for Dense Object Detection

Knowledg Distillation on Object Detection

Deep Semantic Face Deblurring

Generative Adversarial Networks and Probabilistic Graph Models for Hyperspectral Image Classification

On the insufficiency of existing momentum schemes for Stochastic Optimization

SegmentbeforeDetect: Vehicle Detection and Classification through Semantic Segmentation of Aerial Images

SqueezeNet: AlexNetLevel Accuracy with 50X Fewer Parameters and <0.5MB Model Size

Recurrent Autoregressive Networks for Online MultiObject Tracking

The Building Blocks of Interpretability

IM2HEIGHT: Height Estimation from Single Monocular Imagery via Fully Residual ConvolutionalDeconvolutional Network

Snapshot Ensembles: Train 1, get M for free

Vector Field Based Neural Networks

An Unsupervised Learning Model for Deformable Medical Image Registration

Learning both Weights and Connections for Efficient Neural Networks

Building Instance Classification Using Street View Images

Data Distillation: Towards OmniSupervised Learning

Bayesian image quality transfer with CNNs: Exploring uncertainty in dMRI superresolution

CS294: Deep Reinforcement Learning

Reinforcement learning crash course

Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting

Neural Architecture Search with Reinforcement Learning

2D3D CNN for Cardiac Segmentation

Learning Aerial Image Segmentation from Online Maps

FiberNET: An Ensemble Deep Learning Framework for Clustering White Matter Fibers

Faster RCNN

SegFlow

Twoframe motion estimation based on polynomial expansion

Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

Designing Deep Convolutional Neural Networks for Continuous Object Orientation Estimation

Clustering with Deep Learning: Taxonomy and New Methods

Convolutional Recurrent Neural Networks for Hyperspectral Data Classification

Matching Networks for One Shot Learning

Gradients explode  Deep Networks are shallow  ResNet explained

Dynamic Routing Between Capsules

(NiN) Network In Network

SBNet: Sparse Block Network for Fast Inference

Hyperspectral Image Spatial SuperResolution via 3D Full Convolutional Neural Network

Unsupervised Transformation Learning via Convex Relaxations

Direct White Matter Bundle Segmentation using Stacked UNets

Transforming Autoencoders

Deep Reinforcement Learningbased Image Captioning with Embedding Reward

FullCNN : Striving for Simplicity: The All Convolutional Net

Simultaneous SuperResolution and CrossModality Synthesis of 3D Medical Images using WeaklySupervised Joint Convolutional Sparse Coding

Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

Convolutional neural network architecture for geometric matching

Aggregated Residual Transformations for Deep Neural Networks

WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation

SVP : Surveillance Video Parsing with Single Frame Supervision

Deep Pyramidal Residual Networks

Learning from Simulated and Unsupervised Images through Adversarial Training

DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents

PhotoRealistic Single Image SuperResolution Using a Generative Adversarial Network

Gated Feedback Refinement Network for Dense Image Labeling

Joint Sequence Learning and CrossModality Convolution for 3D Biomedical Segmentation

Universal adversarial perturbations

GSNN : The More You Know: Using Knowledge Graphs for Image Classification

Mask RCNN

Growing a Brain: FineTuning by Increasing Model Capacity

Speed/accuracy tradeoffs for modern convolutional object detectors

Episodic CAMN: Contextual Attentionbased Memory Networks With Iterative Feedback For Scene Labeling

SemiSupervised Monocular Depth Map Prediction

PolyNet: A Pursuit of Structural Diversity in Very Deep Networks

Unsupervised Learning of Depth and EgoMotion from Video

Mimicking Very Efficient Network for Object Detection

Oriented Response Networks

Multigrid Neural Architectures

Inverse Compositional Spatial Transformer Networks

Stacked Generative Adversarial Networks

FRNN: FullResolution Residual Networks for Semantic Segmentation in Street Scenes

Pixelwise Instance Segmentation with a Dynamically Instantiated Network

LCNN: Lookupbased CNN

Deep Watershed Transform for Instance Segmentation

Boundaryaware Instance Segmentation

InstanceLevel Salient Object Segmentation

Dynamic EdgeConditioned Filters in Convolutional Neural Networks on Graphs

Kernel pooling for Convolutional Neural Network

FusionSeg: Learning to Combine Motion and Appearance for Fully Automatic Segmentation of Generic Objects in Videos

Deep Level Sets for Salient Object Detection

Full Resolution Image Compression with Recurrent Neural Networks

Scene Parsing through ADE20K dataset

S3Pool  Pooling with stochastic Spatial Sampling

AFastRCNN: Hard Positive Generation via Adversary for Object Detection

Video Propagation Networks

Dilated Residual Networks

ScaleAware Face Detection

Evolving Neural Networks Through Augmenting Topologies

The Marginal Value of Adaptive Gradient Methods

TiramisuNet: The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation

Inceptionv3 : Rethinking the Inception Architecture for Computer Vision

DelugeNet : Deep Networks with Massive and Flexible Crosslayer Information Inflows

Fast RCNN

UNet + ResNet : The Importance of Skip Connections in Biomedical Image Segmentation

RCNN : Rich feature hierarchies for accurate object detection and semantic segmentation

Overfeat : Integrated Recognition, Localization and Detection using Convolutional Networks

SharpMask : Learning to Refine Object Segments

DeepMask : Learning to Segment Object Candidates

Codebook: Background modeling and subtraction by codebook construction

Kmeans: RealTime Adaptive Foreground/Background Segmentation

Feature Pyramid Networks for Object Detection

PCA: A Bayesian Computer Vision System for Modeling Human Interactions

Learning a similarity metric discriminatively, with application to face verification

DenseNet : Densely Connected Convolutional Networks

Learning Deconvolution Network for Semantic Segmentation

KDE: Nonparametric model for background subtraction

FCNN: Fully Convolutional Networks for Semantic Segmentation

GMM: Learning patterns of activity using realtime tracking

LeNet : GradientBased Learning Applied to Document Recognition

CS229: Machine Learning

GoogLeNet, Inception (Going Deeper with Convolutions)

Layer Normalization

Xception: Deep Learning with Depthwise Separable Convolutions

VggNet: Very Deep Convolutional Networks for LargeScale Image Recognition

ResNet: Deep Residual Learning for Image Recognition

ImagetoImage Translation with Conditional Adversarial Networks

AlexNet: ImageNet Classification with Deep Convolutional Neural Networks

You Only Look Once: Unified, RealTime Object Detection (YOLO)

A Survey on Deep Learning in Medical Image Analysis

SSD: Single Shot MultiBox Detector

UNet Convolutional Networks for Biomedical Image Segmentation

VNet : Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

Batch normalization: Accelerating deep network training by reducing internal covariate shift

CS231n: Convolutional Neural Networks for Visual Recognition
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