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Instance Segmentation

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하위 태스크: 17
평가표: 36
보존된 평가 기록: 338

Instance Segmentation is a computer vision task that involves identifying and separating individual objects within an image, including detecting the boundaries of each object and assigning a unique label to each object. The goal of instance segmentation is to produce a pixel-wise segmentation map of the image, where each pixel is assigned to a specific object instance.

Image Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Jyxarthur/OCLR_model

공식 코드

Segmenting Moving Objects via an Object-Centric Layered Representation

https://github.com/KAIST-Visual-AI-Group/PartSTAD

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PartSTAD: 2D-to-3D Part Segmentation Task Adaptation

https://github.com/KIT-IAI/EasyMLServe

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EasyMLServe: Easy Deployment of REST Machine Learning Services

https://github.com/KaihuaTang/Long-Tailed-Recognition.pytorch

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Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect

https://github.com/Kainmueller-Lab/PatchPerPix

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PatchPerPix for Instance Segmentation

https://github.com/Kainmueller-Lab/shift_equivariance_unet

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How Shift Equivariance Impacts Metric Learning for Instance Segmentation

https://github.com/KangchengLiu/FAC_Foreground_Aware_Contrast

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Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast

https://github.com/KangchengLiu/RM3D

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A Data-efficient Framework for Robotics Large-scale LiDAR Scene Parsing

https://github.com/KevinCortacero/Kartezio

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Kartezio: Evolutionary Design of Explainable Pipelines for Biomedical Image Analysis

https://github.com/KiveeDong/CentripetalNet

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CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection

https://github.com/KyanChen/RSPrompter

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RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model

https://github.com/LandskapeAI/triplet-attention

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Rotate to Attend: Convolutional Triplet Attention Module

https://github.com/LaoYang1994/SOGNet

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SOGNet: Scene Overlap Graph Network for Panoptic Segmentation

https://github.com/Layjins/BoxSeg

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BoxSeg: Quality-Aware and Peer-Assisted Learning for Box-supervised Instance Segmentation

https://github.com/LiWentomng/BoxInstSeg

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Box2Mask: Box-supervised Instance Segmentation via Level-set Evolution

https://github.com/Limingxing00/MitoEM2021-Challenge

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Advanced Deep Networks for 3D Mitochondria Instance Segmentation

https://github.com/Linxius/UrbanScene3D

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Capturing, Reconstructing, and Simulating: the UrbanScene3D Dataset

https://github.com/Lonepic/SPIB

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Point Cloud Instance Segmentation with Semi-supervised Bounding-Box Mining

https://github.com/Madave94/multi-annotator-toolkit

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Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations

https://github.com/MalongTech/research-fad

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Representation Sharing for Fast Object Detector Search and Beyond

https://github.com/MasterBin-IIAU/UNINEXT

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Universal Instance Perception as Object Discovery and Retrieval

https://github.com/Megvii-BaseDetection/DisAlign

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Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

https://github.com/MenghaoGuo/-EANet

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Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks

https://github.com/Microsoft/human-pose-estimation.pytorch

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Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/MinghanLi/STMask

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Spatial Feature Calibration and Temporal Fusion for Effective One-stage Video Instance Segmentation

https://github.com/MiraPurkrabek/BBoxMaskPose

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Detection, Pose Estimation and Segmentation for Multiple Bodies: Closing the Virtuous Circle

https://github.com/MonashAI/LIT

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Less is More: Pay Less Attention in Vision Transformers

https://github.com/MrGiovanni/UNetPlusPlus

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UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

https://github.com/Mukaffi28/ExplainableAI-PotatoGAN-Cutting-Edge-Disease-Identification-for-Potatoes

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PotatoGANs: Utilizing Generative Adversarial Networks, Instance Segmentation, and Explainable AI for Enhanced Potato Disease Identification and Classification

https://github.com/NVIDIA/pix2pixHD

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High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

https://github.com/NesterukSergey/segmentation_image_augmentation

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Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case

https://github.com/NeurAI-Lab/UniNet

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UniNet: A Unified Scene Understanding Network and Exploring Multi-Task Relationships through the Lens of Adversarial Attacks

https://github.com/OmkarThawakar/MSSTS-VIS

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Video Instance Segmentation via Multi-scale Spatio-temporal Split Attention Transformer

https://github.com/OpenMask3D/openmask3d

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OpenMask3D: Open-Vocabulary 3D Instance Segmentation

https://github.com/PJLallen/InstanceSAM2Eval

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Evaluation Study on SAM 2 for Class-agnostic Instance-level Segmentation

https://github.com/PKU-EPIC/GAPartNet

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GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.