wuyang556/CV-News

Summarize the paper and code in Semantation(Semantic Segmentation,2D Medical Segmentation,3D Medical Segmentation,Instance Segmentation,Panoptic Segmentation)

CV-News

• Semantation
• Classification
• Graph Neural Networks
• Super-Resolution
• Registration
• Survey
• Dataset
• Conference and Journal

Segmentation

• Semantic Segmentation
• 2D Medical Segmentation
• 3D Medical Segmentation
• Instance Segmentation
• Panoptic Segmentation
• Video Segmentation

Semantic Segmentation

2019

• CVPR2019
  • Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation[Tensorflow][Pytorch]
  • Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images[oral]
  • Bidirectional Learning for Domain Adaptation of Semantic Segmentation(Apr 2019)[Pytoch]
  • DFANet：Deep Feature Aggregation for Real-Time Semantic Segmentation[Pytoch]
  • Seamless Scene Segmentation
  • Bidirectional Learning for Domain Adaptation of Semantic Segmentation(Apr 2019)[Code]
  • Dual Attention Network for Scene Segmentation(Sep 2018)[Pytorch]
  • Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation
  • In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving Images(Mar 2019))[Pytroch]
  • Structured Knowledge Distillation for Semantic Segmentation(Mar 2019)
  • Knowledge Adaptation for Efficient Semantic Segmentation(Mar 2019)
  • Cross-Modal Self-Attention Network for Referring Image Segmentation(Apr 2019)
  • Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation
  • CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning
  • FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference
  • A Cross-Season Correspondence Dataset for Robust Semantic Segmentation
  • Large-scale interactive object segmentation with human annotators
  • Deep Modular Co-Attention Networks for Visual Question Answering
  • Enhancing Salient Object Segmentation Through Attention[CVPRW】
• AAAI 2019
  • Learning Fully Dense Neural Networks for Image Semantic Segmentation(May 2019)
• ICIP2019
  • Implicit Background Estimation for Semantic Segmentation
  • LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation
• other
  • ELKPPNet: An Edge-aware Neural Network with Large Kernel Pyramid Pooling for Learning Discriminative Features in Semantic Segmentation
  • Hard Pixels Mining: Learning Using Privileged Information for Semantic Segmentation
  • ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation[Pytorch]
  • Recurrent U-Net for Resource-Constrained Segmentation
  • Topology-Preserving Deep Image Segmentation
  • Show, Match and Segment: Joint Learning of Semantic Matching and Object Co-segmentation
  • DiCENet: Dimension-wise Convolutions for Efficient Networks
  • Cross-view Semantic Segmentation for Sensing Surroundings
  • NAS-FCOS: Fast Neural Architecture Search for Object Detection
  • Gated CRF Loss for Weakly Supervised Semantic Image Segmentation
  • Seeing Behind Things: Extending Semantic Segmentation to Occluded Regions
  • Zero-Shot Semantic Segmentation
  • Consistency regularization and CutMix for semi-supervised semantic segmentation
  • RGB and LiDAR fusion based 3D Semantic Segmentation for Autonomous Driving
  • Zero-Shot Semantic Segmentation
  • Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation
  • Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation
  • Incorporating Human Domain Knowledge in 3D LiDAR-based Semantic Segmentation
  • U-Net Based Multi-instance Video Object Segmentation(May 2019)
  • Boundary Loss for Remote Sensing Imagery Semantic Segmentation(May 2019)
  • Efficient Ladder-style DenseNets for Semantic Segmentation of Large Images(May 2019)
  • Simultaneous Object Detection and Semantic Segmentation
  • Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Images
  • EdgeSegNet: A Compact Network for Semantic Segmentation(May 2019)
  • SEMEDA: Enhancing Segmentation Precision with Semantic Edge Aware Loss
  • Segmenting the Future(Apr 2019)[Code]
  • CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing(Apr 2019)
  • ACE: Adapting to Changing Environments for Semantic Segmentation(Apr 2019)
  • FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation(Mar 2019)[Pytorch]
  • Architecture Search of Dynamic Cells for Semantic Video Segmentation(Apr 2019)
  • Template-Based Automatic Search of Compact Semantic Segmentation Architectures(Apr 2019)
  • DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation(Apr 2019)
  • DADA: Depth-aware Domain Adaptation in Semantic Segmentation(Apr 2019)
  • GFF: Gated Fully Fusion for Semantic Segmentation(Apr 2019)
  • MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based Tasks(Apr 2019)
  • Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation(Apr 2019)
  • The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation(Apr 2019)
  • Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes(Apr 2019)
  • The iterative convolution-thresholding method (ICTM) for image segmentation(Apr 2019)
  • Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields( Apr 2019)

2018

• CVPR 2018

  • Context Encoding for Semantic Segmentation(Mar 2018)
  • DenseASPP for Semantic Segmentation in StreetScenes[Pytorch]
  • PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing(May 2018)
  • Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation
  • DFN:Learning a Discriminative Feature Network for Semantic Segmentation
  • Guided Proofreading of Automatic Segmentations for Connectomics
  • Recurrent Scene Parsing with Perspective Understanding in the Loop
  • Context Contrasted Feature and Gated Multi-scale Aggregation for Scene Segmentation
  • icient interactive annotation of segmentation datasets with polygon rnn++
  • Compassionately Conservative Balanced Cuts for Image Segmentation
  • Dynamic-structured Semantic Propagation Network
  • In-Place Activated BatchNorm for Memory-Optimized Training of DNNs
  • Error Correction for Dense Semantic Image Labeling
  • Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation
  • On the Importance of Label Quality for Semantic Segmentation
  • Referring Image Segmentation via Recurrent Refinement Networks[Code]
  • Learning Superpixels with Segmentation-Aware Affinity Loss
  • Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer
  • Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning
  • Learning Pixel-Level Semantic Affinity With Image-Level Supervision for Weakly Supervised Semantic Segmentation
  • Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing
  • Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation
  • Bootstrapping the Performance of Webly Supervised Semantic Segmentation
  • Normalized Cut Loss for Weakly-Supervised CNN Segmentation
  • Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features
  • Weakly Supervised Instance Segmentation Using Class Peak Response

• ECCV 2018

  • BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation(Aug 2018)
  • ICNet for Real-Time Semantic Segmentation on High-Resolution Images(Apr 2017)[Pytorch]
  • ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation(Mar 2018 )[Pytorch]
  • PSANet: Point-wise Spatial Attention Network for Scene Parsing
  • Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation(Feb 2018)[Deeplab V3+]
  • Adaptive Affinity Fields for Semantic Segmentation(Mar 2018)
  • ExFuse: Enhancing Feature Fusion for Semantic Segmentation(Apr 2018)
  • Unified Perceptual Parsing for Scene Understanding(Jul 2018)
  • Multi-Scale Context Intertwining for Semantic Segmentation

• NeurIPS 2018

  • Searching for Efficient Multi-Scale Architectures for Dense Image Prediction(Sep 2018)[Tensorflow]
  • A Probabilistic U-Net for Segmentation of Ambiguous Images(Jun 2018)
  • DifNet: Semantic Segmentation by DiffusionNetworks(May 2018)

• AAAI 2018

  • Spatial As Deep: Spatial CNN for Traffic Scene Understanding(Dec 2017)
  • Mix-and-Match Tuning for Self-Supervised Semantic Segmentation(Dec 2017)
  • Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
  • A^2-Nets: Double Attention Networks
  • Symbolic Graph Reasoning Meets Convolutions
  • Beyond Grids: Learning Graph Representations for Visual Recognition

• IJCAI 2018

  • High Resolution Feature Recovering for Accelerating Urban Scene Parsing

• Othes

  • [RelationNet: Learning Deep-Aligned Representation for Semantic Image Segmentation][ICPR]
  • CCNet: Criss-Cross Attention for Semantic Segmentation(Nov 2018)[Pytorch]
  • OCNet: Object Context Network for Scene Parsing(Sep 2018)[Pytorch]
  • CGNet: A Light-weight Context Guided Network for Semantic Segmentation(Nov 2018)[Pytorch]
  • ShelfNet for Real-time Semantic Segmentation, Multi-path segmentation network(Nov 2018)[Pytorch]
  • Evaluating Bayesian Deep Learning Methods for Semantic Segmentation(Nov 2018)
  • Improving Semantic Segmentation via Video Propagation and Label RelaxationCode
  • Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation(Mar 2018)
  • Locally Adaptive Learning Loss for Semantic Image Segmentation(Feb 2018)
  • RTSeg: Real-time Semantic Segmentation Comparative Study( Mar 2018)

2017

• CVPR 2017

  • Pyramid Scene Parsing Network(Dec 2016)
  • Dilated Residual Networks(Jun 2016)
  • Convolutional RandomWalk Networks for Semantic Image Segmentation(May 2016)
  • Loss Max-Pooling for Semantic Image Segmentation(Apr 2017)
  • Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes(Nov 2016)
  • Gated Feedback Refinement Network for Dense Image Labeling
  • Refinenet: Multi-path refinement networks for high-resolution semantic segmentation
  • Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF
  • Learning Adaptive Receptive Fields for Deep Image Parsing Network
  • The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation[Workshop]

• ICCV 2017

  • Segmentation-Aware Convolutional Networks Using Local Attention Mask(Mar 2017)
  • Predicting Deeper into the Future of Semantic Segmentation(Mar 2017)
  • FoveaNet: Perspective-aware Urban Scene Parsing(Aug 2017))
  • Dense and Low-Rank Gaussian CRFs Using Deep Embeddings Siddhartha
  • Scale-adaptive Convolutions for Scene Parsing
  • Deep Dual Learning for Semantic Image Segmentation
  • Semi Supervised Semantic Segmentation Using Generative Adversarial Network

• NIPS 2017

  • Learning Affinity via Spatial Propagation Networks
  • Dual Path Networks

• Others

  • Understanding Convolution for Semantic Segmentation[WACV ]
  • Semantic Segmentation with Reverse Attention(Jul 2017)[BMVC]
  • Rethinking Atrous Convolution for Semantic Image Segmentation(Jun 2017)
  • Pixel Deconvolutional Networks(May 2017)

2016

• CVPR 2016
  • Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform(Nov 2015)
  • ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation(Nov 2015)[Workshop][Pytorch]
• ECCV 2016
  • Attention to Scale: Scale-aware Semantic Image Segmentation(Nov 2015)
  • Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation
  • Semantic Object Parsing with Graph LSTM(Mar 2016)
• ICLR 2016
  • Multi-scale context aggregation by dilated convolutions(Nov 2015) [Pytorch]
  • Learning Dense Convolutional Embeddings for Semantic Segmentation(Nov 2015)
• NIPS Workshop
  • Semantic Segmentation using Adversarial Networks(Nov 2016)
• others
  • ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation(Jun 2016)
  • High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks(Apr 2016)
  • PixelNet: Towards a General Pixel-level Architecture(Sep 2016))
  • MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving(Dec 2016)

2015

• CVPR 2015
  • Fully Convolutional Networks for Semantic Segmentation(Nov 2014)
  • Feedforward semantic segmentation with zoom-out features(Dec 2014)
  • Learning to Propose Objects[Project][Pytorch]
  • Hypercolumns for Object Segmentation and Fine-grained Localization
  • Scene Labeling with LSTM Recurrent Neural Networks
  • Weakly supervised semantic segmentation for social images
• ICCV 2015
  • Learning deconvolution network for semantic segmentation(May 2015)
  • Semantic Image Segmentation via Deep Parsing Network(Sep 2015)
• Other
  • Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs(Dec 2014[ICLR][DeepLabv1]
  • U-Net: Convolutional Networks for Biomedical Image Segmentation(May 2015)[MICCAI]
  • SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation(Nov 2015)
  • Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation[NIPS]

Before 2015

• paper
  • Simultaneous Detection and Segmentation(Jul 2014)[ECCV 2014]
  • Dense Segmentation-aware Descriptors[CVPR 2013]
  • Semantic Segmentation with Second-Order Pooling[ECCV2012]
  • Nonparametric Scene Parsing via Label Transfer[TPAMI2011][Project]

2D Medical Segmentation

2019

• MICCAI 2019

  • Anatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders
  • Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation[Pytorch]

• CVPR 2019

  • Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology(Apr 2019)
  • Exploiting Computation Power of Blockchain for Biomedical Image Segmentation(Apr 2019)

• AAAI 2019

  • Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks(Apr 2019)

• ISBI2019

  • A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation(Oct 2018)[Keras]
  • Automated Segmentation of Pulmonary Lobes using Coordination-Guided Deep Neural Networks(Apr 2019)
  • Automatic Pulmonary Lobe Segmentation Using Deep Learning(Mar 2019)
  • Deep Learning with Anatomical Priors: Imitating Enhanced Autoencoders in Latent Space for Improved Pelvic Bone Segmentation in MRI(March 2019)
  • US-net for robust and efficient nuclei instance segmentation(Jan 2019)
  • Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation
  • Mask-RCNN and U-net Ensembled for Nuclei Segmentation(Jan 2019)
  • Using CycleGANs for effectively reducing image variability across OCT devices and improving retinal fluid segmentation
  • U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans
  • SUMNet: Fully Convolutional Model for Fast Segmentation of Anatomical Structures in Ultrasound Volumes
  • Learning Mutually Local-global U-nets For High-resolution Retinal Lesion Segmentation in Fundus Images
  • Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation
  • Residual Pyramid FCN for Robust Follicle Segmentation
  • Classification and Detection in Mammograms with Weak Supervision via Dual Branch Deep Neural(Net Apr 2019)[oral]

• EMBC 2019

  • Ultrasound segmentation using U-Net: learning from simulated data and testing on real data[]
  • RASNet: Segmentation for Tracking Surgical Instruments in Surgical Videos Using Refined Attention Segmentation Network(May 2019)

• MIDI 2019

  • XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation(Apr 2019))[Pytorch]

• SCI

  • Deep Q Learning Driven CT Pancreas Segmentation with Geometry-Aware U-Net(Apr 2019))[IEEE Transactions on Medical Imaging,TMI]
  • CE-Net: Context Encoder Network for 2D Medical Image Segmentation(Mar 2019)[Pytorch][Pytorch2][IEEE Transactions on Medical Imaging,TMI]
  • The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning[IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE]
  • Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation[IEEE Transactions on Medical Imaging,TMI]
  • Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation(May 2019)[IEEE Transactions on Medical Imaging,TMI]
  • NAS-Unet: Neural Architecture Search for Medical Image Segmentation(Apr 2019)[IEEE Access]
  • 3-D Surface Segmentation Meets Conditional Random Fields

• other

  • CaDSS: Cataract Dataset for Semantic Segmentation
  • Multi-Scale Attentional Network for Multi-Focal Segmentation of Active Bleed after Pelvic Fractures
  • Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography
  • Compressed Sensing MRI via a Multi-scale Dilated Residual Convolution Network
  • V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation
  • Multi-scale guided attention for medical image segmentation[Pytorch]
  • Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images
  • A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
  • Deep Dilated Convolutional Nets for the Automatic Segmentation of Retinal Vessels
  • Segmentation of blood vessels in retinal fundus images
  • A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images(May 2019)
  • A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT(May 2019)
  • Dual-branch residual network for lung nodule segmentation(May 2019)
  • A novel algorithm for segmentation of leukocytes in peripheral blood(May 2019)
  • Transfer Learning based Detection of Diabetic Retinopathy from Small Dataset(May 2019)
  • iRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading(May 2019)
  • Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function(May 2019)
  • T-Net: Encoder-Decoder in Encoder-Decoder architecture for the main vessel segmentation in coronary angiography
  • Breast Tumor Classification and Segmentation using Convolutional Neural Networks(May 2019)
  • nnU-Net: Breaking the Spell on Successful Medical Image Segmentation(Apr 2019)[Code]
  • Feature Fusion Encoder Decoder Network For Automatic Liver Lesion Segmentation(Mar 2019)
  • MDU-Net: Multi-scale Densely Connected U-Net for biomedical image segmentation(Dec 2018)
  • Segmentation of the Prostatic Gland and the Intraprostatic Lesions on Multiparametic MRI Using Mask-RCNN(Apr 2019)
  • FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI( Apr 2019)
  • FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentation(https://arxiv.org/abs/1902.03091)
  • Skin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks

2018

• IPMI 2018
  • CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation
• other
  • Attention U-Net: Learning Where to Look for the Pancreas(Apr 2018)[Pytorch]
  • Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images(Aug 2018)[Pytorch]
  • UNet++: A Nested U-Net Architecture for Medical Image Segmentation(Jul 2018)

Before 2018

• MICCAI 2015
  • U-Net: Convolutional Networks for Biomedical Image Segmentation(May 2015)

3D Medical Segmentation

2019

• MICCAI 2019
  • A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation[Pytorch][Pytorch2]
  • Project & Excite Modules for Segmentation of Volumetric Medical Scans[Pytorch]
  • Generative adversarial network for segmentation of motion affected neonatal brain MRI
  • Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation
  • Anatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders
  • Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images
  • PseudoEdgeNet: Nuclei Segmentation only with Point Annotations
  • PHiSeg: Capturing Uncertainty in Medical Image Segmentation
• IPMI
  • Brain Tumor Segmentation on MRI with Missing Modalities(Apr 2019)
• ISBI2019
  • Prostate Segmentation from 3D MRI Using a Two-Stage Model and Variable-Input Based Uncertainty Measure
  • Improving Catheter Segmentation & Localization in 3D Cardiac Ultrasound Using Direction-Fused FCN
• arxiv
  • https://arxiv.org/ftp/arxiv/papers/1906/1906.10486.pdf
  • Scalable Neural Architecture Search for 3D Medical Image Segmentation
  • Enforcing temporal consistency in Deep Learning segmentation of brain MR images
  • 4D CNN for semantic segmentation of cardiac volumetric sequences
  • Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors
  • A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation
  • OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images
  • AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
  • Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks
  • Generative Model-Based Ischemic Stroke Lesion Segmentation
  • Automated Segmentation for Hyperdense Middle Cerebral Artery Sign of Acute Ischemic Stroke on Non-Contrast CT Images(May 2019)
  • 3D Dense Separated Convolution Module for Volumetric Image Analysis(May 2019)
  • [RIU-Net: Embarrassingly simple semantic segmentation of 3D LiDAR point cloud（May 2019)]（https://arxiv.org/abs/1905.08748）
  • 3D Whole Brain Segmentation using Spatially Localized Atlas Network Tiles(Mar 2019)
  • Thickened 2D Networks for 3D Medical Image Segmentation(Apr 2019)
  • Spherical U-Net on Cortical Surfaces: Methods and Applications(Apr 2019)
  • 3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRI(Apr 2019)
  • Fully Automatic Segmentation of 3D Brain Ultrasound: Learning from Coarse Annotations

2018

• MICCAI 2018
  • Multi-Task Learning for Left Atrial Segmentation on GE-MRI(Oct 2018)[Pytorch]

Before 2018

• MICCAI
  • 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation(Jun 2016)

Brain Tissue Segmentation

• Paper
  • Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization
  • 3D Patchwise U-Net with Transition Layers for MR Brain Segmentation(Rank 1)[TensorFlow]
  • MixNet: Multi-modality Mix Network for Brain Segmentation(Rank3)[tensorflow]
  • Robust 3D Convolutional Neural Network with Boundary Correction for Accurate Brain Tissue Segmentation(Rank3)[Keras]
  • Automatic Brain Structures Segmentation Using Deep Residual Dilated U-Net(Rank9)
  • On direct distribution matching for adapting segmentation networks(Apr 2019)[Code]

MS lesion segmentation

• Paper
  • Soft labeling by Distilling Anatomical knowledge for Improved MS Lesion Segmentation(Jan 2019)[ISBI2019]
  • Multiple Sclerosis Lesion Synthesis in MRI using an encoder-decoder U-NET(Jan 2019)
  • Multiple Sclerosis Lesion Inpainting Using Non-Local Partial Convolutions(Dec 2018)
  • A Self-Adaptive Network For Multiple Sclerosis Lesion Segmentation From Multi-Contrast MRI With Various Imaging Protocols(Nov 2018)
  • Multi-branch Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation(Nov 2018)[NeuroImage]
  • Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation((Aug 2018)[MICCAI 2018]

Instance Segmentation

2019

• CVPR 2019
  • Hybrid Task Cascade for Instance Segmentation(Jan 2019)[Pytorch]
  • Pose2Seg: Detection Free Human Instance Segmentation(Mar 2018)[Code]
  • Budget-aware Semi-Supervised Semantic and Instance Segmentation[[Workshop]]
• other
  • A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation
  • Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth[Code]
  • DARNet: Deep Active Ray Network for Building Segmentation
  • YOLACT: Real-time Instance Segmentation(Apr 2019)
  • Concatenated Feature Pyramid Network for Instance Segmentation(Mar 2019)
  • Single Pixel Reconstruction for One-stage Instance Segmentation(Apr 2019
  • Learning Instance Occlusion for Panoptic Segmentation

Panoptic Segmentation

2019

• CVPR2019
  • Attention-guided Unified Network for Panoptic Segmentation
  • UPSNet: A Unified Panoptic Segmentation Network(Apr 2019)[Pytorch]
  • Panoptic Feature Pyramid Networks(Jan 2019[Kaiming He]
  • Interactive Full Image Segmentation by Considering All Regions Jointly
  • Panoptic Segmentation
• other
  • Straight to Shapes++: Real-time Instance Segmentation Made More Accurate(May 2019)
  • DeeperLab: Single-Shot Image Parser(Feb 2019)[[Code]]
  • An End-to-End Network for Panoptic Segmentation(Mar 2019
  • Single Network Panoptic Segmentation for Street Scene Understanding
  • Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network(Feb 2019)
  • Detecting Reflections by Combining Semantic and Instance Segmentation(Apr 2019)
  • PanopticFusion: Online Volumetric Semantic Mapping at the Level of Stuff and Things(March 2019)
  • Class-independent sequential full image segmentation, using a convolutional net that finds a segment within an attention region, given a pointer pixel within this segment(February 2019

2018

• ECCV2018
  • Weakly- and Semi-Supervised Panoptic Segmentation(Aug 2018) other
  • Learning to Fuse Things and Stuff(Dec 2018)

Video-Segmentation

2019

• CVPR 2019
  • Spatiotemporal CNN for Video Object Segmentation(Apr 2019)[Code]
• other
  • Video Instance Segmentation
  • MAIN: Multi-Attention Instance Network for Video Segmentation

Graph Neural Networks

• 2019
  • Neighborhood Enlargement in Graph Neural Networks(May 2019)[Pytorch]
  • A Comparison of Stereo-Matching Cost between Convolutional Neural Network and Census for Satellite Images(May 2019)

Classification

2019

• Exploring Randomly Wired Neural Networks
  • Exploring Randomly Wired Neural Networks for Image Recognition（Apr 2019）[Pyroech]
  • Network Pruning via Transformable Architecture Search(May 2019)[Code]
  • AM-LFS: AutoML for Loss Function Search
  • XNAS: Neural Architecture Search with Expert Advice
• Attention Module
  • AttentionRNN: A Structured Spatial Attention Mechanism(May 2019)
• Knowledge distillation
  • Adversarially Robust Distillation
• CVPR 2019
  • SKNet:Selective Kernel Networks(Mar 2019)[Coffe][Pytorch]
  • HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs(Mar 2019)
  • Bag of Tricks for Image Classification with Convolutional Neural Networks(Dec 2018)[Code]
  • An attention-based multi-resolution model for prostate whole slide imageclassification and localization[CVPRW]
• ICML 2019
  • Making Convolutional Networks Shift-Invariant Again[Code]
  • Self-Attention Graph Pooling
• arXiv
  • Mapped Convolutions[Code]
  • Zero-Shot Image Classification Using Coupled Dictionary Embedding
  • Dense Scale Network for Crowd Counting
  • Efficient N-Dimensional Convolutions via Higher-Order Factorization
  • TensorNetwork for Machine Learning
  • A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks
  • ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition
  • HGC: Hierarchical Group Convolution for Highly Efficient Neural Network
  • Visual Tree Convolutional Neural Network in Image Classification
  • DIANet: Dense-and-Implicit Attention Network[Pytorch]
  • HadaNets: Flexible Quantization Strategies for Neural Networks
  • FAN: Focused Attention Networks
  • Network Deconvolution[Pytorch]
  • SpecNet: Spectral Domain Convolutional Neural Network
  • Multi-Sample Dropout for Accelerated Training and Better Generalization
  • Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks
  • TopoResNet: A hybrid deep learning architecture and its application to skin lesion classification(May 2019)
  • Skin Cancer Recognition using Deep Residual Network(May 2019)
  • Vehicle Shape and Color Classification Using Convolutional Neural Network(May 2019)
  • TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes
  • ISBNet: Instance-aware Selective Branching Network
  • Convolutional neural networks with fractional order gradient method(May 2019)
  • Searching for MobileNetV3[Pytorch]
  • High Frequency Residual Learning for Multi-Scale Image Classification
  • Seesaw-Net: Convolution Neural Network With Uneven Group Convolution
  • TextCaps: Handwritten Character Recognition With Very Small Datasets(Apr 2019)[Keras][WACV]
  • Self-Attention Capsule Networks for Image Classification
  • Analytical Moment Regularizer for Gaussian Robust Networks(Apr 2019)[Pytorch]
  • Deep Sparse Representation-based Classification(Apr 2019)[Code]
  • GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond(Apr 2019)[Pytorch]
  • DenseNet Models for Tiny ImageNet Classification(Apr 2019)
  • Deep Anchored Convolutional Neural Networks(Apr 2019)
  • Stochastic Region Pooling: Make Attention More Expressive(Apr 2019)
  • Attention Augmented Convolutional Networks(Apr 2019)
  • High-Resolution Representations for Labeling Pixels and Regions(Apr 2019)
  • Deep High-Resolution Representation Learning for Human Pose Estimation(Apr 2019)[Pytorch]
  • Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution( Apr 2019)[Pytorch]
  • Convolutional Neural Networks with Layer Reuse
  • Generalizing discrete convolutions for unstructured point clouds(Apr 2019)[Pytorch]
  • Hybrid Cosine Based Convolutional Neural Networks(Apr 2019)
  • Res2Net: A New Multi-scale Backbone Architecture(Apr 2019)
  • G-softmax: Improving Intra-class Compactness and Inter-class Separability of Features(Apr 2019)
  • ANTNets: Mobile Convolutional Neural Networks for Resource Efficient Image Classification(Apr 2019)
  • A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids(Apr 2019)
  • Compressing deep neural networks by matrix product operators(Apr 2019)
  • Local Relation Networks for Image Recognition( Apr 2019)
• 3D
  • Resource Efficient 3D Convolutional Neural Networks(Apr 2019)[Code]

2017

• CVPR 2017
  • DenseNet:Densely Connected Convolutional Networks(Aug 2016)

Super-Resolution

2019

• CVPR 2019
  • 3D Appearance Super-Resolution with Deep Learning[Pytorch]
• Medical
  • Medical image super-resolution method based on dense blended attention network
  • Progressive Generative Adversarial Networks for Medical Image Super resolution(Feb 2019)
  • How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach[ISBI2019]
• Arxiv
  • Lightweight Image Super-Resolution with Adaptive Weighted Learning Network(Apr 2019)[Code]
  • Multi-scale deep neural networks for real image super-resolution(Apr 2019)
  • Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks

2018

• Medical
  • Brain MRI super-resolution using 3D generative adversarial networks(Dec 2018)[MIDL][3D]
  • CT-image Super Resolution Using 3D Convolutional Neural Network(Jun 2018)[3D]
  • Super-resolution MRI through Deep Learning
  • Channel Splitting Network for Single MR Image Super-Resolution

2017

• CVPR 2017
  • Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding(May 2017)
• MICCAI 2017
  • Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
  • DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI

Registration

• arxiv
  • Robust, fast and accurate: a 3-step method for automatic histological image registration(Mar 2019)
  • 3DRegNet: A Deep Neural Network for 3D Point Registration( Apr 2019)
  • Non-Rigid Point Set Registration Networks(Apr 2019)[Pytorch]
  • Automatic Nonrigid Histological Image Registration with Adaptive Multistep Algorithm(Apr 2019)
  • Palmprint image registration using convolutional neural networks and Hough transform(Apr 2019)

Survey

• 2019
  • An Attentive Survey of Attention Models(Apr 2019)
  • Object Detection in 20 Years: A Survey
  • AI in the media and creative industries
  • Advancements in Image Classification using Convolutional Neural Network
  • A Review on Deep Learning in Medical Image Reconstruction

Dataset

Medical

• All Challenges

Brain

• Brain Tissue Segmentation

  • MRBrainS2018
  • iSeg-2017 challenge:segmentation of 6-month infant brain tissues
  • NEATBrainS15
  • MRBrainS2013
  • NeoBrainS2012

• MS Lesion Segmentation

  • 2016 MS segmentation challenge
  • 2015 Longitudinal MS Lesion Segmentation Challenge
  • 2008 MS lesion segmentation challenge

• Multimodal Brain Tumor Segmentation

  • Multimodal Brain Tumor Segmentation Challenge 2018
  • Multimodal Brain Tumor Segmentation Challenge 2017
  • Multimodal Brain Tumor Segmentation Challenge 2016

• Ischemic Stroke Lesion Segmentation

  • Ischemic Stroke Lesion Segmentation (ISLES) 2018
  • Ischemic Stroke Lesion Segmentation (ISLES) 2017
  • Ischemic Stroke Lesion Segmentation (ISLES) 2016
  • Ischemic Stroke Lesion Segmentation (ISLES) 2016

• White Matter Hyperintensities

  • WMH Segmentation Challenge 2017

• EM segmentation challenge

  • ISBI Challenge: Segmentation of neuronal structures in EM stacks

Conference and Journal

Medical Image Processing Conference and Journal

Conference

MICCAI
Submission Deadline：2018-03-02
Accept/Reject Notification：

ISBI
Submission Deadline：Oct 16, 2018
Accept/Reject Notification：Dec 18, 2018

IPMI
Submission Deadline:13 December 2018
Accept/Reject Notification：25 February 2019

EMBC[CCF C]
Submission Deadline:February 19, 2019
Accept/Reject Notification：April 12, 2019

BIBM2019[CCF B]
Submission Deadline: Aug 17, 2019
Accept/Reject Notification：Oct 1, 2019

ICASSP[CCF B]
Submission Deadline:October 29
Accept/Reject Notification：February 1

MIDL
Submission Deadline:17 December 2018
Accept/Reject Notification：27 February 2019

Journal

Medical Image Analysis,MIA
IEEE Transactions on Medical Imaging,TMI

Image Processing Conference and Journal

Conference

CVPR
Submission Deadline：2018-11-16 Accept/Reject Notification： 2019-03-02

ECCV
Submission Deadline：2018-03-14
Accept/Reject Notification：2018-07-01

ICCV Submission Deadline：2019-03-15
Accept/Reject Notification2019-06-07

ICML
Submission Deadline：2019-01-18

ICLR
Submission Deadline：2018-09-27

AAAI
Submission Deadline：2018-08-30
Accept/Reject Notification：2018-11-01

NeurIPS
Submission Deadline：May 23, 2019
Accept/Reject Notification： Dec 2 - Dec 8, 2019

IJCAI
Submission Deadline：2019-02-25
Accept/Reject Notification： 2019-05-09

Journal