Implementation of different class-incremental methods read more of Class Incremental Learning Methods for Visual Tasks

FaVCI2D is a face verification dataset including demographically-diversified faces and challenging negative faces. read more of Face Verification with Challenging Imposters and Diversified Demographics

AdvisIL recommends appropriate algorithm-backbone architecture combinations for a user-provided class-incremental learning scenario. read more of AdvisIL - A Class-Incremental Learning Advisor

Transfer-learning-based method addressing exemplar-free class-incremental learning read more of Feature Translation for Exemplar-Free Class-Incremental Learning

Filter-Pruning of Lightweight Face Detectors Using a Geometric Median Criterion read more of Lightweight Face Detectors

An information flow-preserving knowledge distillation methodology for model compression. read more of InDistill

Provides a framework for learning text-driven generative paths in pre-trained GANs. read more of ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences

Provides a framework for anonymizing faces in public datasets using pre-trained GANs. read more of Attribute-preserving Face Dataset Anonymization via Latent Code Optimization

Provides a framework for discovering non-linear interpretable paths in pre-trained GAN latent spaces. read more of WarpedGANSpace: Finding non-linear RBF paths in GAN latent space

Provides a Neural Face Reenactment framework by leveraging the expressiveness of the StyleGAN2’s style space. read more of StyleMask: Disentangling the Style Space of StyleGAN2 for Neural Face Reenactment

Provides a framework for the problem of Neural Face Reenactment using Generative Adversarial Networks (GANs). read more of HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces