SELFIES solves molecular string representation weaknesses for material design.
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problem Weaknesses in SMILES for representing valid molecules in material design.
method Introducing SELFIES, a 100% robust string-based molecular representation.
result SELFIES strings correspond to valid molecules, allowing arbitrary machine learning applications.
Paper tackles selfie cartoonization with a new GAN.
problem Cartoonization of selfies with artistic abstraction and exaggeration.
method Proposes scGAN with attentive adversarial network (AAN) for specific facial region emphasis.
result Method generates cartoon portraits with improved robustness and different styles.
Selfie pretrains image embeddings without pixel-level predictions.
problem Training image embeddings efficiently with limited labeled data.
method Contrastive Predictive Coding loss for masked patches, using convolutional and attention mechanisms.
result Significant improvement in ResNet-50 accuracy on ImageNet 224 x 224 with 60 examples per class (5%).
Ensuring the security of transactions is currently one of the major challenges that banking systems deal with. The usage of face for biometric authentication of users is attracting large investments from banks worldwide due to its convenience and acceptability by people, especially in cross-domain scenarios, in which f…
GANs can bias synthetic data, affecting minority and female faces.
problem GANs can amplify biases in synthetic data augmentation.
method Examine GANs on face-shots with gender and skin tone biases.
result GANs generate biased synthetic data, skewing minority modes and features.
Paper shows adversarial training can be fooled by new type of noise.
problem Adversarial training can be fooled by new types of noise.
method Designing ADVIN, a new type of inducing noise.
result ADVIN can degrade adversarial training robustness by 99.9%.