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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/visresearch/patchmix

공식 코드

Inter-Instance Similarity Modeling for Contrastive Learning

https://github.com/visual-ai/vclr

공식 코드

v-CLR: View-Consistent Learning for Open-World Instance Segmentation

https://github.com/vitae-transformer/mtp

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MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining

https://github.com/vitae-transformer/samrs

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SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model

https://github.com/vitae-transformer/vitae-vsa

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VSA: Learning Varied-Size Window Attention in Vision Transformers

https://github.com/vlar-group/ogc

공식 코드

OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds

https://github.com/vlar-group/unsupobjseg

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Promising or Elusive? Unsupervised Object Segmentation from Real-world Single Images

https://github.com/w1zheng/dknet

공식 코드

3D Instances as 1D Kernels

https://github.com/w1zheng/insteacher3d

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Instance Consistency Regularization for Semi-Supervised 3D Instance Segmentation

https://github.com/wangbo-zhao/2022cvpr-mmmmtbvs

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Modeling Motion with Multi-Modal Features for Text-Based Video Segmentation

https://github.com/wangck20/v2m

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V2M: Visual 2-Dimensional Mamba for Image Representation Learning

https://github.com/wanggrun/Adaptively-Connected-Neural-Networks

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Adaptively Connected Neural Networks

https://github.com/wangsr126/RDSNet

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RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation

https://github.com/waterscenes/waterscenes

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WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces

https://github.com/wayveai/fiery

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FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras

https://github.com/weiguangzhao/PBNet

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Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization

https://github.com/weijiawu/cisdq

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Continual Learning for Image Segmentation with Dynamic Query

https://github.com/weizhenfrank/weaknucleiseg

공식 코드

Weakly Supervised Nuclei Segmentation via Instance Learning

https://github.com/wenhe-jia/tive

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TIVE: A Toolbox for Identifying Video Instance Segmentation Errors

https://github.com/wenz116/lang2seg

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Referring Expression Object Segmentation with Caption-Aware Consistency

https://github.com/wesleyhsieh0806/ss-prl

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Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond

https://github.com/westgate458/xb-net

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Training a universal instance segmentation network for live cell images of various cell types and imaging modalities

https://github.com/whai362/PVT

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Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

https://github.com/wimlds-trojmiasto/detect-waste

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Waste detection in Pomerania: non-profit project for detecting waste in environment

https://github.com/windygoo/pathcontext

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Towards Effective and Efficient Context-aware Nucleus Detection in Histopathology Whole Slide Images

https://github.com/windygoo/promptnucseg

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Unleashing the Power of Prompt-driven Nucleus Instance Segmentation

https://github.com/wizaca23/BBBC006-Instance-Segmentation

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Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images

https://github.com/wjf5203/SeqFormer

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SeqFormer: Sequential Transformer for Video Instance Segmentation

https://github.com/wjf5203/vnext

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In Defense of Online Models for Video Instance Segmentation

https://github.com/wjn922/referformer

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Language as Queries for Referring Video Object Segmentation

https://github.com/wl-zhao/VPD

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Unleashing Text-to-Image Diffusion Models for Visual Perception

https://github.com/wofmanaf/SA-Net

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SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

https://github.com/workforai/UniLSeg

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Universal Segmentation at Arbitrary Granularity with Language Instruction

https://github.com/wudongming97/onlinerefer

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OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation

https://github.com/wusize/f-lmm

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F-LMM: Grounding Frozen Large Multimodal Models

https://github.com/wuyongjiancode/cyclic

공식 코드

Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation

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