Alex won the Best Paper Award at the Continual Learning Workshop at CVPR 2022 for his paper Continually Learning Self-Supervised Representations with Projected Functional Regularization. Francesco and Saurav received the runner-up award for:
Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization.
Joost van de Weijer gave an invited talk at Continual Learning Workshop.
Yaxing’s paper on Distilling GANs with Style-Mixed Triplets for X2I Translation with Limited Data is accepted on ICLR 2022.
We have a total of four workshop papers at the CLVISION workshop at CVPR 2022.
We also have one additional paper at Efficient Deep Learning for Computer Vision CVPR Workshop 2022:
Kai’s paper on HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification is accepted at BMVC 2021.
Also Javad’s paper Class-Balanced Active Learning for Image Classification got accepted at WACV 2022.
Shiqi has one paper at the NeurIPS 2021 Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation.
Check out our new framework for analysis of class-incremental learning (FACIL), which contains implementations of fourteen class-incremental algorithms and several baselines. It allows you to reproduce our results on CIFAR 100 presented in our survey paper.
Two papers have been accepted for the main track: Yaxing’s paper on TransferI2I: Transfer Learning for Image-to-Image Translation from Small Datasets. And Shiqi’s paper on Generalized Source-free Domain Adaptation (see project page).
Fei’s paper Slimmable compressive autoencoders for practical neural image compression has been accepted for CVPR.
Also four CVPR workshop papers have been accepted:
Riccardo’s paper >RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning on continual learning of captioning systems, and Yaxing’s paper on transfer learning for image-to-image systems:DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs have been accepted !
