https://github.com/yonghyun-ahn/line-out-of-distribution-detection-by-leveraging-important-neurons
공식 코드LINe: Out-of-Distribution Detection by Leveraging Important Neurons
Papers with Code 아카이브
Out-of-Distribution Detection
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Detect out-of-distribution or anomalous examples.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yookoon/density_uncertainty_layers
공식 코드Density Uncertainty Layers for Reliable Uncertainty Estimation
https://github.com/yuxiaoleemarks/cma
공식 코드Concept Matching with Agent for Out-of-Distribution Detection
https://github.com/yyliu01/rpl
공식 코드Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation
https://github.com/zaharah/ood_audio
공식 코드On Out-of-Distribution Detection for Audio with Deep Nearest Neighbors
https://github.com/zhenzhel/lift_map_detect
공식 코드Unsupervised Out-of-Distribution Detection with Diffusion Inpainting
https://github.com/zjlab-ammi/vae4ood
공식 코드Unsupervised Out-of-Distribution Detection by Restoring Lossy Inputs with Variational Autoencoder
https://github.com/zjysteven/mixoe
공식 코드Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments
https://github.com/zjysteven/sio
공식 코드SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection
https://github.com/zxk1212/OODD
공식 코드OODD: Test-time Out-of-Distribution Detection with Dynamic Dictionary
https://gitlab.com/drti/neco
공식 코드https://github.com/0liliulei/hieraseg
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/SSD
SSD: A Unified Framework for Self-Supervised Outlier Detection
https://github.com/2sang/OOD-baseline
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/AI-for-Ocean-Science/ulmo
https://github.com/AlexMeinke/Provable-OOD-Detection
https://github.com/ArthurHoa/deep-eknn
https://github.com/Bennie-Han/Image-augementation-pytorch
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/HenryLHH/HVAE-OOD
https://github.com/HussainAther/potts
https://github.com/IlyaDobrynin/GridMixup
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/JakobCode/UncertaintyInNeuralNetworks_Resources
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/Janus-Shiau/ood_confidence_tensorflow
Learning Confidence for Out-of-Distribution Detection in Neural Networks
https://github.com/JoonHyung-Park/ODIN
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
https://github.com/Kaushal28/CutMix-Regularization-using-PyTorch
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/LingAndZero/CADRef
CADRef: Robust Out-of-Distribution Detection via Class-Aware Decoupled Relative Feature Leveraging
https://github.com/MacroMayhem/OnMixup
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
https://github.com/Mephisto405/Unsupervised-Out-of-Distribution-Detection-by-Maximum-Classifier-Discrepancy
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy
https://github.com/Mind23-2/MindCode-3/tree/main/MIMO-UNet
Probabilistic MIMO U-Net: Efficient and Accurate Uncertainty Estimation for Pixel-wise Regression
https://github.com/PaddlePaddle/PaddleClas
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/Pilhyeon/Learning-Action-Completeness-from-Points
Weakly-supervised Temporal Action Localization by Uncertainty Modeling
https://github.com/PsorTheDoctor/microarray-data
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/ShiyuLiang/odin-pytorch
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
https://github.com/SimonThomine/MixedTeacher
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization
https://github.com/StanfordASL/SCOD
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.