Papers with Code 아카이브

Age Estimation

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하위 태스크: 1
평가표: 16
보존된 평가 기록: 109

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/Kasumigaoka-Utaha/Pytorch-implementation-of-DeepRegressionForests

Deep Regression Forests for Age Estimation

https://github.com/StevenBanama/C3AE

C3AE: Exploring the Limits of Compact Model for Age Estimation

https://github.com/ThomasWangY/2024-AAAI-HPT

Learning to Prompt for Vision-Language Models

https://github.com/Vill-Lab/2024-TIP-MetaPrompt

Learning to Prompt for Vision-Language Models

https://github.com/Vishal-V/GSoC-TensorFlow-2019/blob/master/face_app/model.py

Face Aging With Conditional Generative Adversarial Networks

https://github.com/YangYongJin/APEX

Learning to Prompt for Vision-Language Models

https://github.com/abhiexo/Deep_Learning-2

Face Aging With Conditional Generative Adversarial Networks

https://github.com/ahmed127011/RNDF

Facial age estimation by deep residual decision making

https://github.com/azshue/TPT

Learning to Prompt for Vision-Language Models

https://github.com/bazilas/matconvnet-deepReg

Robust Optimization for Deep Regression

https://github.com/changsukim-ku/order-learning

https://github.com/chenqiang19/vgg_real_app_age_regression

On the effect of age perception biases for real age regression

https://github.com/ck37/coral-ordinal

Rank consistent ordinal regression for neural networks with application to age estimation

https://github.com/farinamatteo/zero

Learning to Prompt for Vision-Language Models

https://github.com/gaobb/DLDL-v2

Learning Expectation of Label Distribution for Facial Age and Attractiveness Estimation

https://github.com/healthx-lab/biomedcoop

Learning to Prompt for Vision-Language Models

https://github.com/hhenryd/tap

Learning to Prompt for Vision-Language Models

https://github.com/jung-jun-uk/mixface

K-FACE: A Large-Scale KIST Face Database in Consideration with Unconstrained Environments

https://github.com/kaiyangzhou/on-device-dg

Learning to Prompt for Vision-Language Models

https://github.com/karaposu/facexformer-pipeline

FaceXFormer: A Unified Transformer for Facial Analysis

https://github.com/kenomo/industrial-clip

Learning to Prompt for Vision-Language Models

https://github.com/mlvlab/dapt

Learning to Prompt for Vision-Language Models

https://github.com/mshehrozsajjad/Age-Classification

Rank consistent ordinal regression for neural networks with application to age estimation

https://github.com/muzairkhattak/multimodal-prompt-learning

Learning to Prompt for Vision-Language Models

https://github.com/muzairkhattak/protext

Learning to Prompt for Vision-Language Models

https://github.com/ruidaniel/rbaca

Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristics

https://github.com/saic-fi/bayesian-prompt-learning

Learning to Prompt for Vision-Language Models

https://github.com/senguptaumd/SfSNet

An All-In-One Convolutional Neural Network for Face Analysis

https://github.com/shenwei1231/caffe-DeepRegressionForests

Deep Regression Forests for Age Estimation

https://github.com/shridharrhegde/vgg-age

Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model

https://github.com/srvcodes/clap4clip

Learning to Prompt for Vision-Language Models

https://github.com/umgupta/2d-slice-set-networks

Improved Brain Age Estimation with Slice-based Set Networks

https://github.com/vill-lab/2024-aaai-hpt

Learning to Prompt for Vision-Language Models

https://github.com/yangyucheng000/papercode-2/tree/main/TAA_MindSpore-main

TAA-GCN: A Temporally Aware Adaptive Graph Convolutional Network for Age Estimation

https://huggingface.co/lion-ai/MedImageInsights

MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging

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