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/huyquoctrinh/kdas

공식 코드

KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp Segmentation

https://github.com/huyquoctrinh/kdas3

공식 코드

KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp Segmentation

https://github.com/huyquoctrinh/mediaeval2020

공식 코드

Refined Deep Neural Network and U-Net for Polyps Segmentation

https://github.com/hvcl/ScribbleCont

공식 코드

Scribble-supervised Cell Segmentation Using Multiscale Contrastive Regularization

https://github.com/hvision-nku/cascade-clip

공식 코드

Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation

https://github.com/hvision-nku/conv2former

공식 코드

Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition

https://github.com/hvision-nku/maskclippp

공식 코드

MaskCLIP++: A Mask-Based CLIP Fine-tuning Framework for Open-Vocabulary Image Segmentation

https://github.com/hwansoo-choi/cognitive-transfuser

공식 코드

Cognitive TransFuser: Semantics-guided Transformer-based Sensor Fusion for Improved Waypoint Prediction

https://github.com/hwei-hw/generalist_vision_foundation_models_for_medical_imaging

공식 코드

Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical Segmentation

https://github.com/hy0523/mtnet

공식 코드

Learning Motion and Temporal Cues for Unsupervised Video Object Segmentation

https://github.com/hydragon516/dpa

공식 코드

Dual Prototype Attention for Unsupervised Video Object Segmentation

https://github.com/hydragon516/gsanet

공식 코드

Guided Slot Attention for Unsupervised Video Object Segmentation

https://github.com/hynnsk/PPAP

공식 코드

Progressive Proxy Anchor Propagation for Unsupervised Semantic Segmentation

https://github.com/hynnsk/hp

공식 코드

Leveraging Hidden Positives for Unsupervised Semantic Segmentation

https://github.com/hyunjunChhoi/Balanced_Energy

공식 코드

Balanced Energy Regularization Loss for Out-of-distribution Detection

https://github.com/hyunwoo137/edaformer

공식 코드

Embedding-Free Transformer with Inference Spatial Reduction for Efficient Semantic Segmentation

https://github.com/hyunwoo137/metaseg

공식 코드

MetaSeg: MetaFormer-based Global Contexts-aware Network for Efficient Semantic Segmentation

https://github.com/hyz-xmaster/swa_object_detection

공식 코드

SWA Object Detection

https://github.com/hzhupku/ifa

공식 코드

Learning Implicit Feature Alignment Function for Semantic Segmentation

https://github.com/hzhupku/semiseg-ael

공식 코드

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning

https://github.com/hzlbbfrog/bgcrack

공식 코드

Infrastructure Crack Segmentation: Boundary Guidance Method and Benchmark Dataset

https://github.com/hzlbbfrog/crackmamba

공식 코드

Mamba meets crack segmentation

https://github.com/hzxie/RMNet

공식 코드

Efficient Regional Memory Network for Video Object Segmentation

https://github.com/hzykent/JSENet

공식 코드

JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds

https://github.com/hzykent/VMNet

공식 코드

VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation

https://github.com/hzykent/lidal

공식 코드

LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation

https://github.com/i-sahajmistry/nnunet_brats2023

공식 코드

Multiscale Encoder and Omni-Dimensional Dynamic Convolution Enrichment in nnU-Net for Brain Tumor Segmentation

https://github.com/iMED-Lab/OCTA-Net-OCTA-Vessel-Segmentation-Network

공식 코드

Physiology-based simulation of the retinal vasculature enables annotation-free segmentation of OCT angiographs

https://github.com/iVMCL/AOGNet-v2

공식 코드

Attentive Normalization

https://github.com/iamjackyan/fed-lwr

공식 코드

A New Perspective to Boost Performance Fairness for Medical Federated Learning

https://github.com/iannunes/coreseg

공식 코드

Conditional Reconstruction for Open-set Semantic Segmentation

https://github.com/iannunes/fuss

공식 코드

FuSS: Fusing Superpixels for Improved Segmentation Consistency

https://github.com/iantsen/hecktor

공식 코드

Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images

https://github.com/iasakit3t/shifnet

공식 코드

Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

https://github.com/ibm/multimodal-3d-image-segmentation

공식 코드

FNOSeg3D: Resolution-Robust 3D Image Segmentation with Fourier Neural Operator

https://github.com/ibm/neural-embedding-compression

공식 코드

Neural Embedding Compression For Efficient Multi-Task Earth Observation Modelling

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