Age-Invariant Face Recognition
5 papers with code • 4 benchmarks • 3 datasets
Age-invariant face recognition is the task of performing face recognition that is invariant to differences in age.
( Image credit: Look Across Elapse )
Network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur.
Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
Benchmarking our model on one of the most popular unconstrained face recognition datasets IJB-C additionally verifies the promising generalizability of AIM in recognizing faces in the wild.
To reduce such a discrepancy, in this paper we propose a novel algorithm to remove age-related components from features mixed with both identity and age information.
We further validate MTLFace on two popular general face recognition datasets, showing competitive performance for face recognition in the wild.
On this basis, we formulate predictions as a mapping from parents' genetic factors to children's genetic factors, and disentangle them from external and variety factors.