Facial Attribute Classification
11 papers with code • 6 benchmarks • 9 datasets
Facial attribute classification is the task of classifying various attributes of a facial image - e.g. whether someone has a beard, is wearing a hat, and so on.
( Image credit: Multi-task Learning of Cascaded CNN for Facial Attribute Classification )
Benchmarks
These leaderboards are used to track progress in Facial Attribute Classification
Datasets
UTKFace
MORPH
FairFace
bFFHQ
CelebV-HQ
IMDB-Clean
A View From Somewhere (AVFS)
Most implemented papers
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age
Images were collected from the YFCC-100M Flickr dataset and labeled with race, gender, and age groups.
Learning from Failure: Training Debiased Classifier from Biased Classifier
Neural networks often learn to make predictions that overly rely on spurious correlation existing in the dataset, which causes the model to be biased.
Adversarial Information Factorization
ToniCreswell/attribute-cVAEGAN
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ICLR 2019
We propose a novel generative model architecture designed to learn representations for images that factor out a single attribute from the rest of the representation.
Imbalanced Deep Learning by Minority Class Incremental Rectification
In particular, existing deep learning methods consider mostly either class balanced data or moderately imbalanced data in model training, and ignore the challenge of learning from significantly imbalanced training data.
Fair Contrastive Learning for Facial Attribute Classification
sungho-coolg/fscl
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CVPR 2022
Through extensive experiments on CelebA and UTK Face, we validate that the proposed method significantly outperforms SupCon and existing state-of-the-art methods in terms of the trade-off between top-1 accuracy and fairness.
Discover and Mitigate Unknown Biases with Debiasing Alternate Networks
By training in an alternate manner, the discoverer tries to find multiple unknown biases of the classifier without any annotations of biases, and the classifier aims at unlearning the biases identified by the discoverer.
Training Debiased Subnetworks with Contrastive Weight Pruning
parkgeonyeong/dcwp
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CVPR 2023
Neural networks are often biased to spuriously correlated features that provide misleading statistical evidence that does not generalize.
Consistency and Accuracy of CelebA Attribute Values
Two annotators independently assigning attribute values shows that only 12 of 40 common attributes are assigned values with >= 95% consistency, and three (high cheekbones, pointed nose, oval face) have essentially random consistency.
MARLIN: Masked Autoencoder for facial video Representation LearnINg
ControlNet/MARLIN
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CVPR 2023
This paper proposes a self-supervised approach to learn universal facial representations from videos, that can transfer across a variety of facial analysis tasks such as Facial Attribute Recognition (FAR), Facial Expression Recognition (FER), DeepFake Detection (DFD), and Lip Synchronization (LS).
MiVOLO: Multi-input Transformer for Age and Gender Estimation
Age and gender recognition in the wild is a highly challenging task: apart from the variability of conditions, pose complexities, and varying image quality, there are cases where the face is partially or completely occluded.
