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Found 4 papers, 1 papers with code
Meta Variance Transfer: Learning to Augment from the Others
Humans have the ability to robustly recognize objects with various factors of variations such as nonrigid transformation, background noise, and change in lighting conditions.
Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization
As recent advances in mobile camera technology have enabled the capability to capture high-resolution images, such as 4K images, the demand for an efficient deblurring model handling large motion has increased.
Quality-Agnostic Image Recognition via Invertible Decoder
Our two-stage scheme allows the network to produce clean-like and robust features from any quality images, by reconstructing their clean images via the invertible decoder.
Ranked #17 on
Domain Generalization
on ImageNet-C
DiscFace: Minimum Discrepancy Learning for Deep Face Recognition
Softmax-based learning methods have shown state-of-the-art performances on large-scale face recognition tasks.
Ranked #1 on
Face Verification
on CALFW
