Papers with Code 아카이브

2D Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

17

평가표

11

보존된 평가 기록

42

코드

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

https://github.com/songchangwei/3dct-sd-ivh-ich

공식 코드

HemSeg-200: A Voxel-Annotated Dataset for Intracerebral Hemorrhages Segmentation in Brain CT Scans

https://github.com/songw-zju/Meta-RangeSeg

공식 코드

Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature Aggregation

https://github.com/songxinhang/D-CNN

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Depth CNNs for RGB-D scene recognition: learning from scratch better than transferring from RGB-CNNs

https://github.com/soolab/simcis

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Rethinking Query-based Transformer for Continual Image Segmentation

https://github.com/sophiabano/endovis-fetreg2021

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Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings

https://github.com/sophieostmeier/uncertainsmallempty

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USE-Evaluator: Performance Metrics for Medical Image Segmentation Models with Uncertain, Small or Empty Reference Annotations

https://github.com/sotiraslab/AgileFormer

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AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation

https://github.com/sotiraslab/SC-VAE

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SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTA

https://github.com/sotiraslab/dlk

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D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation

https://github.com/soumbane/dualselfdistillation

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Volumetric medical image segmentation through dual self-distillation in U-shaped networks

https://github.com/soumickmj/pulaski

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PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation

https://github.com/souro/multilingual_text_detoxification

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Text Detoxification as Style Transfer in English and Hindi

https://github.com/souro/multilingual_tst

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Multilingual Text Style Transfer: Datasets & Models for Indian Languages

https://github.com/souro/tst_llm

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Are Large Language Models Actually Good at Text Style Transfer?

https://github.com/spamlab/data_sharing

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Relict landslide detection using Deep-Learning architectures for image segmentation in rainforest areas: A new framework

https://github.com/speechbrain/speechbrain

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Posthoc Interpretation via Quantization

https://github.com/speedinghzl/CCNet

공식 코드

CCNet: Criss-Cross Attention for Semantic Segmentation

https://github.com/spengliang/weakm3d

공식 코드

WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection

https://github.com/spidernitt/sam-pm

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SAM-PM: Enhancing Video Camouflaged Object Detection using Spatio-Temporal Attention

https://github.com/spla-tam/splatam

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SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM

https://github.com/splinterli/sattca

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Scale-aware Test-time Click Adaptation for Pulmonary Nodule and Mass Segmentation

https://github.com/spyflying/CMPC-Refseg

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Referring Image Segmentation via Cross-Modal Progressive Comprehension

https://github.com/spyflying/LSCM-Refseg

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Linguistic Structure Guided Context Modeling for Referring Image Segmentation

https://github.com/sqbqamar/SAMA-UNet

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SAMA-UNet: Enhancing Medical Image Segmentation with Self-Adaptive Mamba-Like Attention and Causal-Resonance Learning

https://github.com/sr0920/cit-net

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CiT-Net: Convolutional Neural Networks Hand in Hand with Vision Transformers for Medical Image Segmentation

https://github.com/sr0920/tec-net

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TEC-Net: Vision Transformer Embrace Convolutional Neural Networks for Medical Image Segmentation

https://github.com/ssen7/histo_cap_generation_2

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Automatic Report Generation for Histopathology images using pre-trained Vision Transformers

https://github.com/ssen7/histo_cap_transformers

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Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERT

https://github.com/sshaoshuai/PointCloudDet3D

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From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network

https://github.com/ssyc123/siseg

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Synthetic Instance Segmentation from Semantic Image Segmentation Masks

https://github.com/ssyc123/tfiseg

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Synthetic Instance Segmentation from Semantic Image Segmentation Masks

https://github.com/sta8is/dino-foresight

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$\texttt{DINO-Foresight}$: Looking into the Future with DINO

https://github.com/stamatisalex/ovenet

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OVeNet: Offset Vector Network for Semantic Segmentation

https://github.com/stanfordmlgroup/CheXseg

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CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation

https://github.com/stanfordmlgroup/auto-generate-wls

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Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation

https://github.com/stanley-313/imagesegfm-survey

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Image Segmentation in Foundation Model Era: A Survey

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