Density Map Distillation for Incremental Object Counting

no code implementations • 11 Apr 2023 • Chenshen Wu, Joost Van de Weijer

We investigate the problem of incremental learning for object counting, where a method must learn to count a variety of object classes from a sequence of datasets.

Incremental Learning Object +1

Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification

1 code implementation • 4 Oct 2022 • Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost Van de Weijer

Lifelong object re-identification incrementally learns from a stream of re-identification tasks.

Knowledge Distillation Metric Learning +1

MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains

1 code implementation • 28 Apr 2021 • Yaxing Wang, Abel Gonzalez-Garcia, Chenshen Wu, Luis Herranz, Fahad Shahbaz Khan, Shangling Jui, Joost Van de Weijer

Therefore, we propose a novel knowledge transfer method for generative models based on mining the knowledge that is most beneficial to a specific target domain, either from a single or multiple pretrained GANs.

Transfer Learning

Generative Feature Replay For Class-Incremental Learning

1 code implementation • 20 Apr 2020 • Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost Van de Weijer

To prevent forgetting, we combine generative feature replay in the classifier with feature distillation in the feature extractor.

Class Incremental Learning Image Generation +1

Memory Replay GANs: Learning to Generate New Categories without Forgetting

1 code implementation • NeurIPS 2018 • Chenshen Wu, Luis Herranz, Xialei Liu, Yaxing Wang, Joost Van de Weijer, Bogdan Raducanu

In particular, we investigate generative adversarial networks (GANs) in the task of learning new categories in a sequential fashion.

Memory Replay GANs: learning to generate images from new categories without forgetting

1 code implementation • 6 Sep 2018 • Chenshen Wu, Luis Herranz, Xialei Liu, Yaxing Wang, Joost Van de Weijer, Bogdan Raducanu

In particular, we investigate generative adversarial networks (GANs) in the task of learning new categories in a sequential fashion.

Transferring GANs: generating images from limited data

1 code implementation • ECCV 2018 • Yaxing Wang, Chenshen Wu, Luis Herranz, Joost Van de Weijer, Abel Gonzalez-Garcia, Bogdan Raducanu

Transferring the knowledge of pretrained networks to new domains by means of finetuning is a widely used practice for applications based on discriminative models.

10-shot image generation Domain Adaptation +1