Papers with Code 아카이브

Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

29

평가표

150

보존된 평가 기록

1,918

코드

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

https://github.com/adnan-cas/atrouslora

공식 코드

VesselSAM: Leveraging SAM for Aortic Vessel Segmentation with AtrousLoRA

https://github.com/adonis-galaxy/dspoint

공식 코드

DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion

https://github.com/adri-romsor/iterative_inference_segm

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Image Segmentation by Iterative Inference from Conditional Score Estimation

https://github.com/advdfacd/AggMask

공식 코드

SODAR: Segmenting Objects by DynamicallyAggregating Neighboring Mask Representations

https://github.com/adynathos/attentropy

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AttEntropy: On the Generalization Ability of Supervised Semantic Segmentation Transformers to New Objects in New Domains

https://github.com/aecelaya/MIST

공식 코드

PocketNet: A Smaller Neural Network for Medical Image Analysis

https://github.com/aecelaya/gen-surf-loss

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A Generalized Surface Loss for Reducing the Hausdorff Distance in Medical Imaging Segmentation

https://github.com/aecelaya/mg-nets

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FMG-Net and W-Net: Multigrid Inspired Deep Learning Architectures For Medical Imaging Segmentation

https://github.com/aeitel/self_deepmask

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Self-supervised Transfer Learning for Instance Segmentation through Physical Interaction

https://github.com/aerorobotics/caltech-aerial-rgbt-dataset

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Caltech Aerial RGB-Thermal Dataset in the Wild

https://github.com/afeng-x/smt

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Scale-Aware Modulation Meet Transformer

https://github.com/agaldran/kpis

공식 코드

KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level

https://github.com/agaldran/lesion_losses_ood

공식 코드

On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution Robustness

https://github.com/agis85/multimodal_segmentation

공식 코드

Disentangle, align and fuse for multimodal and semi-supervised image segmentation

https://github.com/agosl/Orthogonal_Ensemble_Networks

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Orthogonal Ensemble Networks for Biomedical Image Segmentation

https://github.com/agroboticsresearch/sdm-d

공식 코드

Learn from Foundation Model: Fruit Detection Model without Manual Annotation

https://github.com/aharley/segaware

공식 코드

Segmentation-Aware Convolutional Networks Using Local Attention Masks

https://github.com/ahmad-shirazi/docparsenet

공식 코드

DocParseNet: Advanced Semantic Segmentation and OCR Embeddings for Efficient Scanned Document Annotation

https://github.com/ahme0307/streoscene

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2018 Robotic Scene Segmentation Challenge

https://github.com/ahukui/BOWDANet

공식 코드

Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation

https://github.com/ahukui/SIPNet

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Selective Information Passing for MR/CT Image Segmentation

https://github.com/ai-application-and-integration-lab/omtseg

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Open-Vocabulary Panoptic Segmentation Using BERT Pre-Training of Vision-Language Multiway Transformer Model

https://github.com/ai-med/halos

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HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgery

https://github.com/ai-med/squeeze_and_excitation

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`Project & Excite' Modules for Segmentation of Volumetric Medical Scans

https://github.com/ai4ce/BAGSFit

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Primitive Fitting Using Deep Boundary Aware Geometric Segmentation

https://github.com/ai4colonoscopy/pranet-v2

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PraNet-V2: Dual-Supervised Reverse Attention for Medical Image Segmentation

https://github.com/ai4luc/cerradata-4mm

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CerraData-4MM: A multimodal benchmark dataset on Cerrado for land use and land cover classification

https://github.com/aiconslab/roodmri

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ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI

https://github.com/aidialab/retifluidnet

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RetiFluidNet: A Self-Adaptive and Multi-Attention Deep Convolutional Network for Retinal OCT Fluid Segmentation

https://github.com/aielte-research/MedSegPretrainImageNet

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Enhancing pretraining efficiency for medical image segmentation via transferability metrics

https://github.com/aieson/crossmatch

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CrossMatch: Enhance Semi-Supervised Medical Image Segmentation with Perturbation Strategies and Knowledge Distillation

https://github.com/aigeeksgroup/sss

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SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation

https://github.com/aijinrjinr/mlb-seg

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Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation

https://github.com/ailab-cvc/groupmixformer

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Advancing Vision Transformers with Group-Mix Attention

https://github.com/ailab-cvc/unireplknet

공식 코드

UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition

https://github.com/ailab-cvc/yolo-world

공식 코드

YOLO-World: Real-Time Open-Vocabulary Object Detection

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