Facial Attribute Classification
17 papers with code • 7 benchmarks • 10 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
LFWA
bFFHQ
CelebV-HQ
IMDB-Clean
A View From Somewhere (AVFS)
Most implemented papers
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.
Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems
Recently, various studies have presented machine unlearning algorithms and evaluated their methods on several datasets.
Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender Estimation
Furthermore, we attempted various ways to fine-tune the ShareGPT4V model for this specific task, aiming to achieve state-of-the-art results in this particular challenge.
Distributionally Generative Augmentation for Fair Facial Attribute Classification
heqianpei/diga
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This work proposes a novel, generation-based two-stage framework to train a fair FAC model on biased data without additional annotation.
