https://github.com/yangyucheng000/-insightface
Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression
Papers with Code 아카이브
regression
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 15
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yangyucheng000/Paper-3/tree/main/RCR_MindSpore
RCR: Robust Compound Regression for Robust Estimation of Errors-in-Variables Model
https://github.com/yaoyao-liu/mini-imagenet-tools
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
https://github.com/yaringal/DropoutUncertaintyExps
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
https://github.com/yaringal/multi-task-learning-example
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
https://github.com/yeefan1999/Explainable-Health-Prediction-with-Transfer-Learning
Age Progression/Regression by Conditional Adversarial Autoencoder
https://github.com/yeliudev/R2-Tuning
https://github.com/yicli/API
Automated Problem Identification: Regression vs Classification via Evolutionary Deep Networks
https://github.com/yilun-wu/MetaL-Benchmark
Meta-Learning Priors for Efficient Online Bayesian Regression
https://github.com/yliess86/Bayeformers
https://github.com/ymcui/Chinese-ELECTRA
https://github.com/yoboget/AdversarialRegression
https://github.com/yoonholee/MT-net
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
https://github.com/yoonsanghyu/VAE_for_regression_PyTorch
Variational AutoEncoder For Regression: Application to Brain Aging Analysis
https://github.com/youdao-ai/SRNet
https://github.com/youmi-zym/AcfNet
Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching
https://github.com/younggns/comparative-abusive-lang
One-step and Two-step Classification for Abusive Language Detection on Twitter
https://github.com/yredwood/fewshot_blogpost
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
https://github.com/yromano/fair_dummies
https://github.com/yuhaonankaka/adl_maskrcnn
ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
https://github.com/yumaloop/CV_report2019
https://github.com/yunyishen/mssl
Simultaneous Transformation and Rounding (STAR) Models for Integer-Valued Data
https://github.com/yuriak/PPDAI
https://github.com/yuriautsumi/PersonalizedGP
Personalized Gaussian Processes for Future Prediction of Alzheimer's Disease Progression
https://github.com/yutian8328/federatedlearning
https://github.com/yuxumin/CoRe
Group-aware Contrastive Regression for Action Quality Assessment
https://github.com/zerenyenice/spsa-fsr
SPSA-FSR: Simultaneous Perturbation Stochastic Approximation for Feature Selection and Ranking
https://github.com/zhangxiutao/ROLO
Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking
https://github.com/zhanhuijing/ECC_PYCHARM
https://github.com/zhenyx19/medmnist
MedMNIST Classification Decathlon: A Lightweight AutoML Benchmark for Medical Image Analysis
https://github.com/zhimingzo/modulated-gcn
Semantic Graph Convolutional Networks for 3D Human Pose Regression
https://github.com/zhou13/symmetrynet
https://github.com/zlf1993/cy
https://github.com/zoj613/polya-gamma
Bayesian inference for logistic models using Polya-Gamma latent variables
https://github.com/zs7779/FAN_AdaptiveWingLoss
Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
https://github.com/zyf12389/GC-Net
End-to-End Learning of Geometry and Context for Deep Stereo Regression
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.