README.md

Segmentation

• Semantic Segmentation
• Instance Segmentation
• Panoptic Segmentation
• Video Segmentation
• Saliency Detection

Semantic Segmentation

2019

• CVPR 2019
  • Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning
  • Pattern-Affinitive Propagation across Depth, Surface Normal and Semantic Segmentation
  • Cross-Modal Relationship Inference for Grounding Referring Expressions
  • Face Parsing with RoI Tanh-Warping
  • Speech2Face: Learning the Face Behind a Voice
  • Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images [code]
  • Budget-aware Semi-Supervised Semantic and Instance Segmentation [Workshop]
  • DARNet: Deep Active Ray Network for Building Segmentation
  • Zoom To Learn, Learn To Zoom
  • A Simple Pooling-Based Design for Real-Time Salient Object Detection
  • Pyramid Feature Attention Network for Saliency detection [code]
  • Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation [code]
  • Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot Learning [code]
  • SCOPS: Self-Supervised Co-Part Segmentation
  • Panoptic Feature Pyramid Networks
  • Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning [code]
  • Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More
  • Data-Driven Neuron Allocation for Scale Aggregation Networks
  • Bi-Directional Cascade Network for Perceptual Edge Detection [code]
  • Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation
  • DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
  • Devil is in the Edges: Learning Semantic Boundaries from Noisy Annotations
  • Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology
  • Pixel-Adaptive Convolutional Neural Networks
  • A Relation-Augmented Fully Convolutional Network for Semantic Segmentation in Aerial Scenes
  • Cross-Modal Self-Attention Network for Referring Image Segmentation [From NLP]
  • Graphonomy: Universal Human Parsing via Graph Transfer Learning [code]
  • Large-scale interactive object segmentation with human annotators
  • In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving Images
  • A Cross-Season Correspondence Dataset for Robust Semantic Segmentation
  • Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation [code]
  • Knowledge Adaptation for Efficient Semantic Segmentation
  • Structured Knowledge Distillation for Semantic Segmentation
  • FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference
  • Data augmentation using learned transforms for one-shot medical image segmentation
  • Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation
  • Graph-Based Global Reasoning Networks [GCN]
  • T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor [Face Part Seg]
  • Improving Semantic Segmentation via Video Propagation and Label Relaxation
• other 19'conferences
  • CE-Net: Context Encoder Network for 2D Medical Image Segmentation [TMI]
  • Tree-structured Kronecker Convolutional Network for Semantic Segmentation [ICME]
• ICCV 2019
  • Incremental Class Discovery for Semantic Segmentation with RGBD Sensing
  • Asymmetric Non-local Neural Networks for Semantic Segmentation
  • Exploiting temporal consistency for real-time video depth estimation∗
  • Action recognition with spatial-temporal discriminative filter banks
  • Temporal Knowledge Propagation for Image-to-Video Person Re-identification
  • Semi-Supervised Video Salient Object Detection Using Pseudo-Labels
  • LIP: Local Importance-based Pooling
  • Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation
  • Metric Learning With HORDE: High-Order Regularizer for Deep Embeddings [code]
  • Similarity-Preserving Knowledge Distillation
  • Expectation-Maximization Attention Networks for Semantic Segmentation
  • Orientation-aware Semantic Segmentation on Icosahedron Spheres
  • Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking
  • Learning Lightweight Lane Detection CNNs by Self Attention Distillation [code]
• arXiv
  • Consensus Feature Network for Scene Parsing
  • Deep Co-Training for Semi-Supervised Image Segmentation
  • Residual Pyramid Learning for Single-Shot Semantic Segmentation
  • What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing
  • Dynamic Deep Networks for Retinal Vessel Segmentation
  • Efficient Smoothing of Dilated Convolutions for Image Segmentation
  • Adaptive Masked Weight Imprinting for Few-Shot Segmentation
  • An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutions
  • Lift-the-Flap: Context Reasoning Using Object-Centered Graphs
  • Fast-SCNN: Fast Semantic Segmentation Network
  • THE EFFECT OF SCENE CONTEXT ON WEAKLY SUPERVISED SEMANTIC SEGMENTATION
  • MultiResUNet : Rethinking the U-Net Architecture for Multimodal Biomedical Image Segmentation
  • On Boosting Semantic Street Scene Segmentation with Weak Supervision

2018

• CVPR 2018

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

• ECCV 2018

  • Multi-Scale Context Intertwining for Semantic Segmentation
  • Unified Perceptual Parsing for Scene Understanding
  • ExFuse: Enhancing Feature Fusion for Semantic Segmentation
  • BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
  • ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
  • PSANet: Point-wise Spatial Attention Network for Scene Parsing
  • ICNet for Real-Time Semantic Segmentation on High-Resolution Images
  • Adaptive Affinity Fields for Semantic Segmentation
  • Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

• Other 18'conferences

  • RelationNet: Learning Deep-Aligned Representation for Semantic Image Segmentation [ICPR]
  • High Resolution Feature Recovering for Accelerating Urban Scene Parsing [IJCAI]
  • Mix-and-Match Tuning for Self-Supervised Semantic Segmentation [AAAI]
  • Spatial As Deep: Spatial CNN for Traffic Scene Understanding Xingang [AAAI]
  • A Probabilistic U-Net for Segmentation of Ambiguous Images [NIPS]
  • DifNet: Semantic Segmentation by Diffusion Networks [NIPS]
  • Beyond Grids: Learning Graph Representations for Visual Recognition [NIPS] [GCN]
  • Symbolic Graph Reasoning Meets Convolutions [NIPS] [GCN]
  • A^2-Nets: Double Attention Networks [NIPS] [GCN]
  • Searching for Efficient Multi-Scale Architectures for Dense Image Prediction [NIPS] [NAS]

• ArXiv

  • Improving Semantic Segmentation via Video Propagation and Label Relaxation
  • Evaluating Bayesian Deep Learning Methods for Semantic Segmentation
  • ShelfNet for Real-time Semantic Segmentation, Multi-path segmentation network
  • CCNet: Criss-Cross Attention for Semantic Segmentation
  • Dual Attention Network for Scene Segmentation
  • Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation
  • Locally Adaptive Learning Loss for Semantic Image Segmentation
  • RTSEG: REAL-TIME SEMANTIC SEGMENTATION COMPARATIVE STUDY
  • OCNet: Object Context Network for Scene Parsing
  • CGNet: A Light-weight Context Guided Network for Semantic Segmentation

2017

• CVPR 2017

  • Convolutional RandomWalk Networks for Semantic Image Segmentation
  • Dilated Residual Networks
  • Learning Adaptive Receptive Fields for Deep Image Parsing Network
  • Loss Max-Pooling for Semantic Image Segmentation
  • Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF
  • Pyramid Scene Parsing Network
  • Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
  • Refinenet: Multi-path refinement networks for high-resolution semantic segmentation
  • Gated Feedback Refinement Network for Dense Image Labeling

• ICCV 2017

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

• Other 17'conferences

  • Understanding Convolution for Semantic Segmentation[WACV]
  • Learning Affinity via Spatial Propagation Networks[NIPS]
  • Dual Path Networks[NIPS]
  • Semantic Segmentation with Reverse Attention[BMVC]
  • The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation[CVPRW]
  • Fully Convolutional Networks for Semantic Segmentation [TPAMI]

• ArXiv

  • Rethinking Atrous Convolution for Semantic Image Segmentation
  • Pixel Deconvolutional Networks

2016

• CVPR 2016

  • Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform

• ECCV 2016

  • Semantic Object Parsing with Graph LSTM
  • Attention to Scale: Scale-aware Semantic Image Segmentation
  • Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

• Other 16'conferences

  • Semantic Segmentation using Adversarial Networks [NIPSW]
  • Speeding up Semantic Segmentation for Autonomous Driving [NIPSW]
  • ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation [PyTorch]
  • Multi-Scale Context Aggregation by Dilated Convolutions [ICLR] [PyTorch]
  • Learning Dense Convolutional Embeddings for Semantic Segmentation[ICLR]

• ArXiv

  • ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
  • PixelNet: Towards a General Pixel-level Architecture
  • MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
  • High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks

2015

• CVPR 2015

  • Fully Convolutional Networks for Semantic Segmentation
  • Hypercolumns for Object Segmentation and Fine-grained Localization
  • Weakly supervised semantic segmentation for social images
  • Scene Labeling with LSTM Recurrent Neural Networks
  • Learning to Propose Objects [PyTorch] [Project]
  • Feedforward semantic segmentation with zoom-out features

• ICCV 2015

  • Semantic Image Segmentation via Deep Parsing Network
  • Learning deconvolution network for semantic segmentation

• Other 15'conferences

  • U-Net: Convolutional Networks for Biomedical Image Segmentation[MICCAI]
  • Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation[NIPS]

• ArXiv

  • SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Before 2015

• Simultaneous Detection and Segmentation [ECCV2014]
• Nonparametric Scene Parsing via Label Transfer [TPAMI2011][Project]
• Dense Segmentation-aware Descriptors[CVPR2013]
• Semantic Segmentation with Second-Order Pooling [ECCV2012]

Repos

• https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
• https://github.com/meetshah1995/pytorch-semseg [PyTorch]

Instance Segmentation

• Learning to Segment Object Candidates
• Recurrent Instance Segmentation [ECCV2016]
• Instance-aware Semantic Segmentation via Multi-task Network Cascades
• Learning to Refine Object Segments
• Fully Convolutional Instance-aware Semantic Segmentation
• Mask R-CNN

Panoptic Segmentation

• Panoptic Segmentation
• Single Network Panoptic Segmentation for Street Scene Understanding
• DeeperLab: Single-Shot Image Parser
• An End-to-End Network for Panoptic Segmentation

Video Segmentation

2018

• CVPR 2018

  • Actor and Action Video Segmentation from a Sentence [project]
  • Dynamic Video Segmentation Network
  • Semantic Video Segmentation by Gated Recurrent Flow Propagation
  • Deep Spatio-Temporal Random Fields for Efficient Video Segmentation [code]
  • Low-Latency Video Semantic Segmentation
  • CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF
  • Efficient Video Object Segmentation via Network Modulation [code]
  • Instance Embedding Transfer to Unsupervised Video Object Segmentation
  • Fast Video Object Segmentation by Reference-Guided Mask Propagation [code]
  • Fast and Accurate Online Video Object Segmentation via Tracking Parts [code]
  • Reinforcement Cutting-Agent Learning for Video Object Segmentation
  • Blazingly Fast Video Object Segmentation With Pixel-Wise Metric Learning
  • MoNet: Deep Motion Exploitation for Video Object Segmentation
  • Motion-Guided Cascaded Refinement Network for Video Object Segmentation

• others

  • Clockwork Convnets for Video Semantic Segmentation (ECCV2016)
  • https://github.com/shelhamer/clockwork-fcn
  • https://github.com/JingchunCheng/Seg-with-SPN
  • http://segmentation.is.tue.mpg.de/

Saliency Detection

• Contextual Encoder-Decoder Network for Visual Saliency Prediction
• Understanding and Visualizing Deep Visual Saliency Models (CVPR2019)
• SAC-Net: Spatial Attenuation Context for Salient Object Detectio

RNN

• ReNet [https://arxiv.org/pdf/1505.00393.pdf]

Graphical Models (CRF, MRF)

• https://github.com/cvlab-epfl/densecrf
• http://vladlen.info/publications/efficient-inference-in-fully-connected-crfs-with-gaussian-edge-potentials/
• http://www.philkr.net/home/densecrf
• http://graphics.stanford.edu/projects/densecrf/
• https://github.com/amiltonwong/segmentation/blob/master/segmentation.ipynb
• https://github.com/jliemansifry/super-simple-semantic-segmentation
• http://users.cecs.anu.edu.au/~jdomke/JGMT/
• https://www.quora.com/How-can-one-train-and-test-conditional-random-field-CRF-in-Python-on-our-own-training-testing-dataset
• https://github.com/tpeng/python-crfsuite
• https://github.com/chokkan/crfsuite
• https://sites.google.com/site/zeppethefake/semantic-segmentation-crf-baseline
• https://github.com/lucasb-eyer/pydensecrf

Datasets:

• Stanford Background Dataset
• Sift Flow Dataset
• Barcelona Dataset
• Microsoft COCO dataset
• MSRC Dataset
• LITS Liver Tumor Segmentation Dataset
• KITTI
• Pascal Context
• Data from Games dataset
• Human parsing dataset
• Mapillary Vistas Dataset
• Microsoft AirSim
• MIT Scene Parsing Benchmark
• COCO 2017 Stuff Segmentation Challenge
• ADE20K Dataset
• INRIA Annotations for Graz-02
• Daimler dataset
• ISBI Challenge: Segmentation of neuronal structures in EM stacks
• INRIA Annotations for Graz-02 (IG02)
• Pratheepan Dataset
• Clothing Co-Parsing (CCP) Dataset
• Inria Aerial Image

other papers

• Ranked List Loss for Deep Metric Learning [CVPR2019]
• Video Generation from Single Semantic Label Map [CVPR2019]
• Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation [CVPR2019]
• Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
• Group-wise Correlation Stereo Network [CVPR2019]
• Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks [CVPR2019]
• Similarity Learning via Kernel Preserving Embedding [AAAI2019]
• Unsupervised Person Re-identification by Soft Multilabel Learning [CVPR2019]
• Learning Robust Representations by Projecting Superficial Statistics Out [ICLR2019]
• MFAS: Multimodal Fusion Architecture Search [CVPR2019]
• SimulCap : Single-View Human Performance Capture with Cloth Simulation [CVPR2019]
• Semantic Image Synthesis with Spatially-Adaptive Normalization [CVPR2019]
• Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection [CVPR2019]
• QATM: Quality-Aware Template Matching For Deep Learning [CVPR2019]
• AdaGraph: Unifying Predictive and Continuous Domain Adaptation through Graphs [CVPR2019]
• Selective Kernel Networks [CVPR2019]
• Towards Robust Curve Text Detection with Conditional Spatial Expansion [CVPR2019]
• Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation [CVPR2019]
• Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration [CVPR2019]
• Networks for Joint Affine and Non-parametric Image Registration [CVPR2019]
• OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations [CVPR2019]
• Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection [CVPR2019]
• Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation [CVPR2019]
• f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning [CVPR2019]
• Residual Non-local Attention Networks for Image Restoration [ICLR2019]
• Self-Supervised Learning via Conditional Motion Propagation [CVPR2019]

Blog posts, other:

• https://handong1587.github.io/deep_learning/2015/10/09/segmentation.html
• http://www.andrewjanowczyk.com/efficient-pixel-wise-deep-learning-on-large-images/
• https://devblogs.nvidia.com/parallelforall/image-segmentation-using-digits-5/
• https://github.com/NVIDIA/DIGITS/tree/master/examples/binary-segmentation
• https://github.com/NVIDIA/DIGITS/tree/master/examples/semantic-segmentation