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20182022
most citedA Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks

213 citations · 230 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV2020

Unveiling Real-Life Effects of Online Photo Sharing

Van-Khoa Nguyen, Adrian Popescu, Jerome Deshayes-Chossart

Social networks give free access to their services in exchange for the right to exploit their users' data. Data sharing is done in an initial context which is chosen by the users.…

cs.CV20203 cited

Initial Classifier Weights Replay for Memoryless Class Incremental Learning

Eden Belouadah, Adrian Popescu, Ioannis Kanellos

Incremental Learning (IL) is useful when artificial systems need to deal with streams of data and do not have access to all data at all times. The most challenging setting requires…

cs.CV2020

Active Class Incremental Learning for Imbalanced Datasets

Eden Belouadah, Adrian Popescu, Umang Aggarwal +1

Incremental Learning (IL) allows AI systems to adapt to streamed data. Most existing algorithms make two strong hypotheses which reduce the realism of the incremental scenario: (1)…

cs.CV2020

Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning

Yannick Le Cacheux, Adrian Popescu, Hervé Le Borgne

Zero-shot learning (ZSL) makes object recognition in images possible in absence of visual training data for a part of the classes from a dataset. When the number of classes is larg…

cs.CV2020

ScaIL: Classifier Weights Scaling for Class Incremental Learning

Eden Belouadah, Adrian Popescu

Incremental learning is useful if an AI agent needs to integrate data from a stream. The problem is non trivial if the agent runs on a limited computational budget and has a bounde…

cs.CV2018

DeeSIL: Deep-Shallow Incremental Learning

Eden Belouadah, Adrian Popescu

Incremental Learning (IL) is an interesting AI problem when the algorithm is assumed to work on a budget. This is especially true when IL is modeled using a deep learning approach,…