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Found 4 papers, 1 papers with code
Lightweight Structure-Aware Attention for Visual Understanding
Vision Transformers (ViTs) have become a dominant paradigm for visual representation learning with self-attention operators.
iLGaCo: Incremental Learning of Gait Covariate Factors
In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset.
Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs
Deep Learning (DL) applications are gaining momentum in the realm of Artificial Intelligence, particularly after GPUs have demonstrated remarkable skills for accelerating their challenging computational requirements.
End-to-End Incremental Learning
Although deep learning approaches have stood out in recent years due to their state-of-the-art results, they continue to suffer from catastrophic forgetting, a dramatic decrease in overall performance when training with new classes added incrementally.
Ranked #2 on
Incremental Learning
on ImageNet100 - 10 steps
(# M Params metric)
