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Semantic Segmentation

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코드

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

https://github.com/zhengxyun/surface-sos

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Surface-SOS: Self-Supervised Object Segmentation via Neural Surface Representation

https://github.com/zhengye1995/Zero-shot-Instance-Segmentation

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Zero-Shot Instance Segmentation

https://github.com/zhengyuan-xie/eccv24_nest

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Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation

https://github.com/zhengzangw/PCS-FUDA

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Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation

https://github.com/zhenxuan-zhang/tucl_brainseg

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Task-oriented Uncertainty Collaborative Learning for Label-Efficient Brain Tumor Segmentation

https://github.com/zhenyuw16/noisyboundaries

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Noisy Boundaries: Lemon or Lemonade for Semi-supervised Instance Segmentation?

https://github.com/zhenzhao/ad-mt

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Alternate Diverse Teaching for Semi-supervised Medical Image Segmentation

https://github.com/zhenzhao/augseg

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Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic Segmentation

https://github.com/zhenzhao/dpms

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Rethinking Data Perturbation and Model Stabilization for Semi-supervised Medical Image Segmentation

https://github.com/zhenzhao/imas

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Instance-specific and Model-adaptive Supervision for Semi-supervised Semantic Segmentation

https://github.com/zhenzhenxiang/SemanticsSharing

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Boosting Real-Time Driving Scene Parsing with Shared Semantics

https://github.com/zhh6425/LocalContextPropagation

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LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers

https://github.com/zhi-xuan-chen/reg2rg

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Large Language Model with Region-guided Referring and Grounding for CT Report Generation

https://github.com/zhichenghuang/cmae

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Contrastive Masked Autoencoders are Stronger Vision Learners

https://github.com/zhifangdeng/missformer

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MISSFormer: An Effective Medical Image Segmentation Transformer

https://github.com/zhiheLu/CWT-for-FSS

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Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer

https://github.com/zhihelu/ending_iss

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Evolving Knowledge Mining for Class Incremental Segmentation

https://github.com/zhijiejia/segdoctor

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Model Doctor for Diagnosing and Treating Segmentation Error

https://github.com/zhijieshen-bjtu/panoformer

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PanoFormer: Panorama Transformer for Indoor 360 Depth Estimation

https://github.com/zhilingyan/medical-sam-bench

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SAMed-2: Selective Memory Enhanced Medical Segment Anything Model

https://github.com/zhimengxin/rcod

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Toward Realistic Camouflaged Object Detection: Benchmarks and Method

https://github.com/zhimin-c/bridge3d

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Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models

https://github.com/zhiqi-li/BEVFormer

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BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

https://github.com/zhiqi-li/Panoptic-SegFormer

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Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers

https://github.com/zhiweihhh/cvpr2022-rvos-challenge

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1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object Segmentation

https://github.com/zhiyuanli218/segret

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SegRet: An Efficient Design for Semantic Segmentation with Retentive Network

https://github.com/zhiyuns/UNITPathSSL

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Nucleus-aware Self-supervised Pretraining Using Unpaired Image-to-image Translation for Histopathology Images

https://github.com/zhongaobo/asymmetry-bts

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Enhancing Incomplete Multi-modal Brain Tumor Segmentation with Intra-modal Asymmetry and Inter-modal Dependency

https://github.com/zhongniuniu/PAMRFuse-plus

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Medical Image Fusion for High-Level Analysis: A Mutual Enhancement Framework for Unaligned PAT and MRI

https://github.com/zhongxuanwang/adv_attk

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Susceptibility of Adversarial Attack on Medical Image Segmentation Models

https://github.com/zhouhuan-hust/lfd-roadseg

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Exploiting Low-level Representations for Ultra-Fast Road Segmentation

https://github.com/zhoul-lab/plhn

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Prototype Learning Guided Hybrid Network for Breast Tumor Segmentation in DCE-MRI

https://github.com/zhoustan/camsam2

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CamSAM2: Segment Anything Accurately in Camouflaged Videos

https://github.com/zhoustan/sam2-vcos

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When SAM2 Meets Video Camouflaged Object Segmentation: A Comprehensive Evaluation and Adaptation

https://github.com/zhouweilian1904/HSI_Segmentation

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When Segmentation Meets Hyperspectral Image: New Paradigm for Hyperspectral Image Classification

https://github.com/zhouyuan888888/sgcpnet

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Real-time Semantic Segmentation via Spatial-detail Guided Context Propagation

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