Papers with Code 아카이브

Semantic Segmentation

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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/lizhuohong/paraformer

공식 코드

Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels

https://github.com/lizhuohong/segland

공식 코드

Generalized Few-Shot Meets Remote Sensing: Discovering Novel Classes in Land Cover Mapping via Hybrid Semantic Segmentation Framework

https://github.com/ljjcoder/PCL

공식 코드

Probabilistic Contrastive Learning for Domain Adaptation

https://github.com/ljjcoder/ehtdi

공식 코드

Exploring High-quality Target Domain Information for Unsupervised Domain Adaptive Semantic Segmentation

https://github.com/ljjcoder/probabilistic-contrastive-learning

공식 코드

Probabilistic Contrastive Learning for Domain Adaptation

https://github.com/ljollans/trunet

공식 코드

Vision Transformers increase efficiency of 3D cardiac CT multi-label segmentation

https://github.com/lkeab/BCNet

공식 코드

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers

https://github.com/lkpengcs/syntumoranalyzer

공식 코드

Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation

https://github.com/llistenl/mlpmatch

공식 코드

Revisiting Network Perturbation for Semi-Supervised Semantic Segmentation

https://github.com/llmir/fedicra

공식 코드

Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation

https://github.com/llmir/fedlppa

공식 코드

FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentation

https://github.com/llmir/yolocurvseg

공식 코드

YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation

https://github.com/lloongx/sfda-cbmt

공식 코드

Source-Free Domain Adaptive Fundus Image Segmentation with Class-Balanced Mean Teacher

https://github.com/lluckyyh/vt-ada

공식 코드

Vision Transformer-based Adversarial Domain Adaptation

https://github.com/lmb-freiburg/diffusion-for-ood

공식 코드

Diffusion for Out-of-Distribution Detection on Road Scenes and Beyond

https://github.com/lmb-freiburg/sf2se3

공식 코드

SF2SE3: Clustering Scene Flow into SE(3)-Motions via Proposal and Selection

https://github.com/lmiapc/fednnu-net

공식 코드

FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation

https://github.com/lmm077/SWEM

공식 코드

SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization

https://github.com/lmmmeng/overlock

공식 코드

OverLoCK: An Overview-first-Look-Closely-next ConvNet with Context-Mixing Dynamic Kernels

https://github.com/lmmmeng/sparx

공식 코드

SparX: A Sparse Cross-Layer Connection Mechanism for Hierarchical Vision Mamba and Transformer Networks

https://github.com/lmmmeng/transxnet

공식 코드

TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition

https://github.com/lmquan2000/mask-mixup

공식 코드

GUNNEL: Guided Mixup Augmentation and Multi-View Fusion for Aquatic Animal Segmentation

https://github.com/locuslab/mdeq

공식 코드

Multiscale Deep Equilibrium Models

https://github.com/lofrienger/curri-afda

공식 코드

Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation

https://github.com/lofrienger/s2me

공식 코드

S$^2$ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentation

https://github.com/lofrienger/single_surgicalscene_for_segmentation

공식 코드

Rethinking Surgical Instrument Segmentation: A Background Image Can Be All You Need

https://github.com/logan-0623/pg-sam

공식 코드

PG-SAM: Prior-Guided SAM with Medical for Multi-organ Segmentation

https://github.com/loicland/superpoint_graph

공식 코드

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

https://github.com/lojzezust/mmsegmentation-macvi

공식 코드

LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark

https://github.com/lojzezust/pansr

공식 코드

PanSR: An Object-Centric Mask Transformer for Panoptic Segmentation

https://github.com/lojzezust/wasr-t

공식 코드

Temporal Context for Robust Maritime Obstacle Detection

https://github.com/lolemacs/iem

공식 코드

Information-Theoretic Segmentation by Inpainting Error Maximization

https://github.com/longmalongma/desa2va

공식 코드

Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder

https://github.com/longyin880815/STCNN

공식 코드

Spatiotemporal CNN for Video Object Segmentation

https://github.com/looooongChen/instance_segmentation_with_pixel_embeddings

공식 코드

Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local Constraints

https://github.com/looooongchen/instseg

공식 코드

Instance Segmentation of Dense and Overlapping Objects via Layering

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