MCIGLE combines aligned multimodal graph features, Fourier feature extraction, and recursive least squares to reduce forgetting in exemplar-free class-incremental graph learning.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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MCIGLE: Multimodal Exemplar-Free Class-Incremental Graph Learning
MCIGLE combines aligned multimodal graph features, Fourier feature extraction, and recursive least squares to reduce forgetting in exemplar-free class-incremental graph learning.