General incremental learning with domain-aware categorical representations
Continual learning is an important problem for achieving human-level intelligence in real-
world applications as an agent must continuously accumulate knowledge in response to …
world applications as an agent must continuously accumulate knowledge in response to …
Fairness continual learning approach to semantic scene understanding in open-world environments
Continual semantic segmentation aims to learn new classes while maintaining the
information from the previous classes. Although prior studies have shown impressive …
information from the previous classes. Although prior studies have shown impressive …
MRN: Multiplexed routing network for incremental multilingual text recognition
Multilingual text recognition (MLTR) systems typically focus on a fixed set of languages,
which makes it difficult to handle newly added languages or adapt to ever-changing data …
which makes it difficult to handle newly added languages or adapt to ever-changing data …
Continual learning for natural language generation in task-oriented dialog systems
Natural language generation (NLG) is an essential component of task-oriented dialog
systems. Despite the recent success of neural approaches for NLG, they are typically …
systems. Despite the recent success of neural approaches for NLG, they are typically …
Text-enhanced data-free approach for federated class-incremental learning
Abstract Federated Class-Incremental Learning (FCIL) is an underexplored yet pivotal issue
involving the dynamic addition of new classes in the context of federated learning. In this …
involving the dynamic addition of new classes in the context of federated learning. In this …
Learning consistent region features for lifelong person re-identification
The lifelong person re-identification (LRe-ID) model retrieves a person across multiple
cameras in continuous data streams and learns new coming datasets incrementally …
cameras in continuous data streams and learns new coming datasets incrementally …
Alife: Adaptive logit regularizer and feature replay for incremental semantic segmentation
We address the problem of incremental semantic segmentation (ISS) recognizing novel
object/stuff categories continually without forgetting previous ones that have been learned …
object/stuff categories continually without forgetting previous ones that have been learned …
Cnll: A semi-supervised approach for continual noisy label learning
N Karim, U Khalid, A Esmaeili… - Proceedings of the …, 2022 - openaccess.thecvf.com
The task of continual learning requires careful design of algorithms that can tackle
catastrophic forgetting. However, the noisy label, which is inevitable in a real-world scenario …
catastrophic forgetting. However, the noisy label, which is inevitable in a real-world scenario …
Continual learning based on ood detection and task masking
Existing continual learning techniques focus on either task incremental learning (TIL) or
class incremental learning (CIL) problem, but not both. CIL and TIL differ mainly in that the …
class incremental learning (CIL) problem, but not both. CIL and TIL differ mainly in that the …
Target: Federated class-continual learning via exemplar-free distillation
This paper focuses on an under-explored yet important problem: Federated Class-Continual
Learning (FCCL), where new classes are dynamically added in federated learning. Existing …
Learning (FCCL), where new classes are dynamically added in federated learning. Existing …