https://github.com/Hzzone/PFA-GAN
공식 코드PFA-GAN: Progressive Face Aging with Generative Adversarial Network
Papers with Code 아카이브
Age Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Age Estimation is the task of estimating the age of a person from an image some other kind of data.
<span style="color:grey; opacity: 0.6">( Image credit: BridgeNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Kartik-3004/facexformer
공식 코드https://github.com/Li-Wanhua/MetaAge
공식 코드https://github.com/Li-Wanhua/POEs
공식 코드Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression
https://github.com/MASILab/BRAID
공식 코드Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease
https://github.com/Milan-BUAA/TSAN-brain-age-estimation
공식 코드Brain Age Estimation From MRI Using Cascade Networks with Ranking Loss
https://github.com/Nicholasli1995/VisualizingNDF
공식 코드https://github.com/Powercoder64/TAA-GCN
공식 코드TAA-GCN: A Temporally Aware Adaptive Graph Convolutional Network for Age Estimation
https://github.com/Raschka-research-group/coral-cnn
공식 코드Rank consistent ordinal regression for neural networks with application to age estimation
https://github.com/YoushanZhang/Adversarial-Regression-Learning-for-Bone-Age-Estimation
공식 코드https://github.com/ZJU-Brain/OTFPF
공식 코드https://github.com/axeber01/dold
공식 코드https://github.com/bintsi/adaptive-graph-learning
공식 코드Multimodal brain age estimation using interpretable adaptive population-graph learning
https://github.com/bintsi/brain-age-population-graphs
공식 코드https://github.com/biomedia-mbzuai/fetalclip
공식 코드FetalCLIP: A Visual-Language Foundation Model for Fetal Ultrasound Image Analysis
https://github.com/brain-age/otfpf
공식 코드https://github.com/chenchao666/Bone-Age-Assessment
공식 코드https://github.com/christianbv/AgeNet
공식 코드https://github.com/davidberend/FairnessMatters
공식 코드Fair and accurate age prediction using distribution aware data curation and augmentation
https://github.com/engrussman/MAVAE
공식 코드https://github.com/ensta-u2is/dido
공식 코드Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression
https://github.com/farzad-bz/harmonizing-flows
공식 코드Harmonizing Flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization
https://github.com/forblindrev/aibias
공식 코드Fair and accurate age prediction using distribution aware data curation and augmentation
https://github.com/gama-ufsc/brain-age
공식 코드Does pre-training on brain-related tasks results in better deep-learning-based brain age biomarkers?
https://github.com/gaobb/DLDL
공식 코드https://github.com/guoyurong0104/crl-code
공식 코드Competing Ratio Loss for Discriminative Multi-class Image Classification
https://github.com/hechmik/voxceleb_enrichment_age_gender
공식 코드https://github.com/humanlab/hart
공식 코드https://github.com/ibug-group/fpage
공식 코드FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild
https://github.com/iman2693/gdsm
공식 코드Brain Age Estimation with a Greedy Dual-Stream Model for Limited Datasets
https://github.com/jacobzhaoziyuan/amr-loss
공식 코드https://github.com/jaygshah/Robust-Brain-Age-Prediction
공식 코드Ordinal Classification with Distance Regularization for Robust Brain Age Prediction
https://github.com/jiawei-ren/BalancedMSE
공식 코드https://github.com/juliojj/app-real-age
공식 코드On the effect of age perception biases for real age regression
https://github.com/kaiyangzhou/coop
공식 코드https://github.com/konstantinkobs/SimLoss
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.