https://github.com/MIC-DKFZ/nnDetection
공식 코드nnDetection: A Self-configuring Method for Medical Object Detection
Papers with Code 아카이브
Semantic Segmentation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MIC-DKFZ/nnunet
공식 코드nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
https://github.com/MICV-yonsei/EAGLE
공식 코드EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation
https://github.com/MIPT-Oulu/mCTSegmentation
공식 코드https://github.com/MJJdG/ULS23
공식 코드https://github.com/MKFMIKU/D2SM
공식 코드https://github.com/MMCheng/SSPC-Net
공식 코드SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network
https://github.com/MMPAN-forms/MMPAN
공식 코드Multi-Modal Association based Grouping for Form Structure Extraction
https://github.com/MMehdiMousavi/AIP
공식 코드AI Playground: Unreal Engine-based Data Ablation Tool for Deep Learning
https://github.com/MMehdiMousavi/SuperCaustics
공식 코드https://github.com/MSiam/AdaptiveMaskedProxies
공식 코드https://github.com/MSiam/TFSegmentation
공식 코드https://github.com/MSiam/motion_adaptation
공식 코드https://github.com/MSiam/video_class_agnostic_segmentation
공식 코드Video Class Agnostic Segmentation with Contrastive Learning for Autonomous Driving
https://github.com/MTLab/MorphMLP
공식 코드MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation Learning
https://github.com/MVIG-SJTU/WSHP
공식 코드Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer
https://github.com/MacavityT/REF-VLM
공식 코드REF-VLM: Triplet-Based Referring Paradigm for Unified Visual Decoding
https://github.com/MalongTech/research-fad
공식 코드Representation Sharing for Fast Object Detector Search and Beyond
https://github.com/Manjuphoenix/IndraEye
공식 코드IndraEye: Infrared Electro-Optical UAV-based Perception Dataset for Robust Downstream Tasks
https://github.com/MansoorehMontazerin/Livelayer-Software
공식 코드https://github.com/MarcBotet/hamlet
공식 코드To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation
https://github.com/MarcelVSHNS/StixelNExT
공식 코드StixelNExT: Toward Monocular Low-Weight Perception for Object Segmentation and Free Space Detection
https://github.com/MarvinLer/tcga_segmentation
공식 코드Weakly supervised multiple instance learning histopathological tumor segmentation
https://github.com/MarvinTeichmann/ConvCRF
공식 코드https://github.com/MarvinTeichmann/MultiNet
공식 코드MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
https://github.com/Masrur02/C-Squared-DA
공식 코드C^2DA: Contrastive and Context-aware Domain Adaptive Semantic Segmentation
https://github.com/MasterBin-IIAU/UNINEXT
공식 코드Universal Instance Perception as Object Discovery and Retrieval
https://github.com/MaterialEyes/Vision_for_Microscopy
공식 코드https://github.com/MathLee/OLBPNet4PFOS
공식 코드Personal Fixations-Based Object Segmentation with Object Localization and Boundary Preservation
https://github.com/MatteoPannacci/SemanticAlignNet-QUAD
공식 코드https://github.com/McGregorWwww/UDTransNet
공식 코드https://github.com/Megvii-BaseDetection/DisAlign
공식 코드Distribution Alignment: A Unified Framework for Long-tail Visual Recognition
https://github.com/MegviiDetection/video_analyst
공식 코드https://github.com/Meituan-AutoML/Twins
공식 코드Twins: Revisiting the Design of Spatial Attention in Vision Transformers
https://github.com/MendelXu/ANN
공식 코드Asymmetric Non-local Neural Networks for Semantic Segmentation
https://github.com/MenghaoGuo/-EANet
공식 코드Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.