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Found 3 papers, 2 papers with code
RealHePoNet: a robust single-stage ConvNet for head pose estimation in the wild
In this work, we address this problem, defined here as the estimation of both vertical (tilt/pitch) and horizontal (pan/yaw) angles, through the use of a single Convolutional Neural Network (ConvNet) model, trying to balance precision and inference speed in order to maximize its usability in real-world applications.
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)
