└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Awesome-Instance-Segmentation[![Awesome](https://awesome.re/badge.svg)](https://awesome.re) 2 | 3 |

4 | 5 | ```diff 6 | - Recent papers (from 2015) 7 | ``` 8 | 9 |

10 | 11 |

Keywords

12 | 13 | 14 | __`img.`__: image level   |   __`vid.`__: video level   |   __`shot.`__: single/few/one shot; |   __`point.`__: point cloud level; |   __`oth.`__: semi-/weakly-/Un-supervised 15 | 16 | Statistics: :fire: code is available & stars >= 100  |  :star: popular & cited in a survey  |  17 | :sunflower: natural scene images  |  :earth_americas: remote sensing images  |  :hospital: medical images 18 | 19 | --- 20 | ## 2020 21 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123460273.pdf)] Conditional Convolutions for Instance Segmentation. [[pytorch](https://github.com/aim-uofa/AdelaiDet)] [__`img.`__] :sunflower: 22 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123460307.pdf)] Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset. [[tensorflow](https://fashionpedia.github.io/home/Model_and_API.html)] [__`img.`__] :hospital: 23 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123480562.pdf)] A General Toolbox for Identifying Object Detection Errors. [[code](https://github.com/dbolya/tide)] [__`img.`__] :sunflower: 24 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510205.pdf)] The Semantic Mutex Watershed for Efficient 25 | Bottom-Up Semantic Instance Segmentation. [__`img.`__] :sunflower: 26 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530188.pdf)] Regression of Instance Boundary by Aggregated CNN and GCN. [__`img.`__] :hospital: 27 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560154.pdf)] STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos. [[pytorch](https://github.com/sabarim/STEm-Seg)] [__`vid.`__] :sunflower: 28 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590001.pdf)] SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation. [[pytorch](https://github.com/JialeCao001/SipMask)] [__`img.`__,__`vid.`__] :sunflower: 29 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590035.pdf)] Learning with Noisy Class Labels for Instance Segmentation. [[pytorch](https://github.com/longrongyang/LNCIS)] [__`img.`__] :sunflower: 30 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530375.pdf)] Commonality-Parsing Network across Shape and Appearance for Partially Supervised Instance Segmentation. [[pytorch](https://github.com/fanq15/FewX)] [__`img.`__] :sunflower: 31 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123550528.pdf)] Point-Set Anchors for Object Detection, Instance Segmentation and Pose Estimation. [__`img.`__] :sunflower: 32 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590715.pdf)] The Devil is in Classification: A Simple Framework for Long-tail Instance Segmentation. [[pytorch](https://github.com/twangnh/SimCal)] [__`img.`__] :sunflower: 33 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123630630.pdf)] SOLO: Segmenting Objects by Locations. [[pytorch](https://github.com/aim-uofa/AdelaiDet)] [__`img.`__] :sunflower: 34 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123680545.pdf)] LevelSet R-CNN: A Deep Variational Method for Instance Segmentation. [__`img.`__] :sunflower: 35 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720613.pdf)] Supervised Edge Attention Network for Accurate Image Instance Segmentation. [[pytorch](https://github.com//IPIU-detection/SEANet)] [__`img.`__] :sunflower: 36 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123630545.pdf)] Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation. [__`point.`__] 37 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123670188.pdf)] Self-Prediction for Joint Instance and Semantic Segmentation of Point Clouds. [__`point.`__] 38 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123750256.pdf)] Instance-Aware Embedding for Point Cloud Instance Segmentation. [__`point.`__] 39 | - [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123540664.pdf)] Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. [__`vid.`__] :sunflower: 40 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Chen_BlendMask_Top-Down_Meets_Bottom-Up_for_Instance_Segmentation_CVPR_2020_paper.html)] BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation. [__`img.`__] :sunflower: 41 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Peng_Deep_Snake_for_Real-Time_Instance_Segmentation_CVPR_2020_paper.html)] Deep Snake for Real-Time Instance Segmentation. [[pytorch](https://github.com/zju3dv/snake/)] [__`img.`__] :sunflower: 42 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Kulikov_Instance_Segmentation_of_Biological_Images_Using_Harmonic_Embeddings_CVPR_2020_paper.html)] Instance Segmentation of Biological Images Using Harmonic Embeddings. [[pytorch](https://github.com/kulikovv/harmonic)] [__`img.`__] :hospital: 43 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Lee_CenterMask_Real-Time_Anchor-Free_Instance_Segmentation_CVPR_2020_paper.html)] CenterMask: Real-Time Anchor-Free Instance Segmentation. [[pytorch](https://github.com/youngwanLEE/CenterMask)] [__`img.`__] :sunflower: 44 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.html)] D2Det: Towards High Quality Object Detection and Instance Segmentation. [[pytorch](https://github.com/JialeCao001/D2Det)] [__`img.`__] :sunflower: 45 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Jiang_PointGroup_Dual-Set_Point_Grouping_for_3D_Instance_Segmentation_CVPR_2020_paper.html)] PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation. [[pytorch](https://github.com/Jia-Research-Lab/PointGroup)] [__`point.`__] 46 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Han_OccuSeg_Occupancy-Aware_3D_Instance_Segmentation_CVPR_2020_paper.html)] OccuSeg: Occupancy-Aware 3D Instance Segmentation. [__`point.`__] 47 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Zhou_Joint_3D_Instance_Segmentation_and_Object_Detection_for_Autonomous_Driving_CVPR_2020_paper.html)] Joint 3D Instance Segmentation and Object Detection for Autonomous Driving. [__`point.`__] 48 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Engelmann_3D-MPA_Multi-Proposal_Aggregation_for_3D_Semantic_Instance_Segmentation_CVPR_2020_paper.html)] PolyTransform: Deep Polygon Transformer for Instance Segmentation. [__`point.`__] 49 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Liang_PolyTransform_Deep_Polygon_Transformer_for_Instance_Segmentation_CVPR_2020_paper.html)] 3D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance Segmentation. [[tensorflow](https://github.com/francisengelmann/3D-MPA)] [__`point.`__] 50 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Jiang_End-to-End_3D_Point_Cloud_Instance_Segmentation_Without_Detection_CVPR_2020_paper.html)] End-to-End 3D Point Cloud Instance Segmentation Without Detection. [__`point.`__] 51 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Ahmed_Density-Based_Clustering_for_3D_Object_Detection_in_Point_Clouds_CVPR_2020_paper.html)] Density-Based Clustering for 3D Object Detection in Point Clouds. [__`point.`__] 52 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Fan_FGN_Fully_Guided_Network_for_Few-Shot_Instance_Segmentation_CVPR_2020_paper.html)] FGN: Fully Guided Network for Few-Shot Instance Segmentation. [__`shot.`__] 53 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Xie_PolarMask_Single_Shot_Instance_Segmentation_With_Polar_Representation_CVPR_2020_paper.html)] PolarMask: Single Shot Instance Segmentation With Polar Representation. [[pytorch](https://github.com/xieenze/PolarMask)] [__`shot.`__] 54 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Zhang_Mask_Encoding_for_Single_Shot_Instance_Segmentation_CVPR_2020_paper.html)] Mask Encoding for Single Shot Instance Segmentation. [[pytorch](https://github.com/aim-uofa/AdelaiDet/)] [__`shot.`__] 55 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Lin_Video_Instance_Segmentation_Tracking_With_a_Modified_VAE_Architecture_CVPR_2020_paper.html)] Video Instance Segmentation Tracking with a Modified VAE Architecture. [__`vid.`__] 56 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Zhou_Learning_Saliency_Propagation_for_Semi-Supervised_Instance_Segmentation_CVPR_2020_paper.html)] Learning Saliency Propagation for Semi-Supervised Instance Segmentation. [[pytorch](https://github.com/ucbdrive/ShapeProp)] [__`oth.`__] :sunflower: 57 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Liu_Unsupervised_Instance_Segmentation_in_Microscopy_Images_via_Panoptic_Domain_Adaptation_CVPR_2020_paper.html)] Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting. [__`oth.`__] :hospital: 58 | - [[AAAI](https://arxiv.org/abs/1912.05070)] RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation. [[pytorch](https://github.com/wangsr126/RDSNet)] [__`img.`__] :sunflower: 59 | - [[AAAI](https://arxiv.org/abs/1911.09199)] Object-Guided Instance Segmentation for Biological Images. [__`img.`__] :hospital: 60 | - [[AAAI](https://arxiv.org/abs/1912.09654)] JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds. [[tensorflow](https://github.com/dlinzhao/JSNet)] [__`point.`__] 61 | 62 | --- 63 | ## 2019 64 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2019/html/Lei_Octree_Guided_CNN_With_Spherical_Kernels_for_3D_Point_Clouds_CVPR_2019_paper.html)] Octree Guided CNN With Spherical Kernels for 3D Point Clouds. [[tensorflow](https://github.com/hlei-ziyan/SPH3D-GCN)] [__`point.`__] 65 | - [[CVPR](https://arxiv.org/abs/1904.00699)] JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields. [[pytorch](https://github.com/pqhieu/JSIS3D)] [__`point.`__] 66 | - [[CVPR](https://arxiv.org/abs/1902.09852)] Associatively Segmenting Instances and Semantics in Point Clouds. [[tensorflow](https://github.com/WXinlong/ASIS)] [__`point.`__] 67 | - [[CVPR](https://arxiv.org/abs/1812.07003)] 3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans. [[pytorch](https://github.com/Sekunde/3D-SIS)] [__`point.`__] 68 | - [[CVPR](https://openaccess.thecvf.com/content_CVPR_2019/papers/Yi_GSPN_Generative_Shape_Proposal_Network_for_3D_Instance_Segmentation_in_CVPR_2019_paper.pdf)] GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud. [[tensorflow](https://github.com/ericyi/GSPN)] [__`point.`__] 69 | - [[ICCV](https://arxiv.org/abs/1906.08650)] 3D Instance Segmentation via Multi-Task Metric Learning. [[tensorflow](https://github.com/lahoud/MTML)] [__`point.`__] 70 | - [[ICCV](https://arxiv.org/abs/1909.11268)] Rescan: Inductive Instance Segmentation for Indoor RGBD Scans. [__`point.`__] 71 | --------------------------------------------------------------------------------