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Class-incremental learning: A survey
Deep models, eg, CNNs and Vision Transformers, have achieved impressive achievements
in many vision tasks in the closed world. However, novel classes emerge from time to time in …
in many vision tasks in the closed world. However, novel classes emerge from time to time in …
Learning without forgetting for vision-language models
Class-Incremental Learning (CIL) or continual learning is a desired capability in the real
world, which requires a learning system to adapt to new tasks without forgetting former ones …
world, which requires a learning system to adapt to new tasks without forgetting former ones …
Data-free sketch-based image retrieval
Rising concerns about privacy and anonymity preservation of deep learning models have
facilitated research in data-free learning. Primarily based on data-free knowledge distillation …
facilitated research in data-free learning. Primarily based on data-free knowledge distillation …
Sddgr: Stable diffusion-based deep generative replay for class incremental object detection
In the field of class incremental learning (CIL) generative replay has become increasingly
prominent as a method to mitigate the catastrophic forgetting alongside the continuous …
prominent as a method to mitigate the catastrophic forgetting alongside the continuous …
Data-free class-incremental hand gesture recognition
This paper investigates data-free class-incremental learning (DFCIL) for hand gesture
recognition from 3D skeleton sequences. In this class-incremental learning (CIL) setting …
recognition from 3D skeleton sequences. In this class-incremental learning (CIL) setting …
VLM-PL: Advanced Pseudo Labeling Approach for Class Incremental Object Detection via Vision-Language Model
In the field of Class Incremental Object Detection (CIOD) creating models that can
continuously learn like humans is a major challenge. Pseudo-labeling methods although …
continuously learn like humans is a major challenge. Pseudo-labeling methods although …
Class-incremental object detection
Deep learning architectures have shown remarkable results in the object detection task.
However, they experience a critical performance drop when they are required to learn new …
However, they experience a critical performance drop when they are required to learn new …
Class-incremental learning via prototype similarity replay and similarity-adjusted regularization
R Chen, G Chen, X Liao, W **ong - Applied Intelligence, 2024 - Springer
The task of incremental learning is to enable machine learning models to continuously learn
and adapt to new tasks and data in changing environments while maintaining knowledge of …
and adapt to new tasks and data in changing environments while maintaining knowledge of …