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/Andreas-Pfeuffer/LSTM-ICNet

공식 코드

Robust Semantic Segmentation in Adverse Weather Conditions by means of Fast Video-Sequence Segmentation

https://github.com/Andrew-Qibin/SPNet

공식 코드

Strip Pooling: Rethinking Spatial Pooling for Scene Parsing

https://github.com/Andrewsher/X-Net

공식 코드

X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies

https://github.com/AngeLouCN/CFPNet-Medicine

공식 코드

CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation

https://github.com/AngeLouCN/DC-UNet

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DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation

https://github.com/AngeLouCN/SAM-2_Surgical_Video

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Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2

https://github.com/AnshShah3009/MetricGold

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MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth Estimation

https://github.com/ArantxaCasanova/ralis

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Reinforced active learning for image segmentation

https://github.com/Arksyd96/synthesis-with-slice-based-ldm

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3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes

https://github.com/Asunatan/LM-Net

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LM-Net: A Light-weight and Multi-scale Network for Medical Image Segmentation

https://github.com/Att100/CP2M

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CP2M: Clustered-Patch-Mixed Mosaic Augmentation for Aerial Image Segmentation

https://github.com/Au3C2/Generator-Versus-Segmentor

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Harmonizing Pathological and Normal Pixels for Pseudo-healthy Synthesis

https://github.com/AutoCompSysLab/DCTNet

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A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-View

https://github.com/AutoML-4Paradigm/AutoSTR

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AutoSTR: Efficient Backbone Search for Scene Text Recognition

https://github.com/AvivNavon/AuxiLearn

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Auxiliary Learning by Implicit Differentiation

https://github.com/BBillot/SynthSeg

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Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and no Retraining

https://github.com/BCV-Uniandes/ROG

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Towards Robust General Medical Image Segmentation

https://github.com/BR-IDL/PaddleViT

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Fully Transformer Networks for Semantic Image Segmentation

https://github.com/BRML/CNNbasedMedicalSegmentation

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CNN-based Segmentation of Medical Imaging Data

https://github.com/Bala93/Context-aware-segmentation

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A context based deep learning approach for unbalanced medical image segmentation

https://github.com/Bala93/Multi-task-deep-network

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Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation

https://github.com/Barrett-python/DuAT

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DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation

https://github.com/Bartzi/kiss

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KISS: Keeping It Simple for Scene Text Recognition

https://github.com/Bartzi/see

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SEE: Towards Semi-Supervised End-to-End Scene Text Recognition

https://github.com/Bartzi/stn-ocr

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STN-OCR: A single Neural Network for Text Detection and Text Recognition

https://github.com/Beckschen/3D-TransUNet

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3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers

https://github.com/Beckschen/TransUNet

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TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

https://github.com/Bhashini-IITJ/visualTranslation

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Show Me the World in My Language: Establishing the First Baseline for Scene-Text to Scene-Text Translation

https://github.com/Big-Brother-Pikachu/Text2Mask

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From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion Models

https://github.com/BinahHu/ADE-FewShot

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Unlocking the Full Potential of Small Data with Diverse Supervision

https://github.com/BirkTorpmannHagen/SegmentationConsistencyTraining

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Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image Segmentation

https://github.com/BorealisAI/CP-VAE

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On Variational Learning of Controllable Representations for Text without Supervision

https://github.com/Bravo5542/TJSTG

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Target-Aware Spatio-Temporal Reasoning via Answering Questions in Dynamics Audio-Visual Scenarios

https://github.com/BrunoSauvalle/AE-NE

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Autoencoder-based background reconstruction and foreground segmentation with background noise estimation

https://github.com/BryanPlummer/pl-clc

공식 코드

Phrase Localization and Visual Relationship Detection with Comprehensive Image-Language Cues

https://github.com/ByungKwanLee/MoAI

공식 코드

MoAI: Mixture of All Intelligence for Large Language and Vision Models

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