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Found 10 papers, 8 papers with code
Join the High Accuracy Club on ImageNet with A Binary Neural Network Ticket
In this work, we revisit the potential of binary neural networks and focus on a compelling but unanswered problem: how can a binary neural network achieve the crucial accuracy level (e. g., 80%) on ILSVRC-2012 ImageNet?
BoolNet: Streamlining Binary Neural Networks Using Binary Feature Maps
Recent works on Binary Neural Networks (BNNs) have made promising progress in narrowing the accuracy gap of BNNs to their 32-bit counterparts, often based on specialized model designs using additional 32-bit components.
BoolNet: Minimizing The Energy Consumption of Binary Neural Networks
Recent works on Binary Neural Networks (BNNs) have made promising progress in narrowing the accuracy gap of BNNs to their 32-bit counterparts.
One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGAN
Generative Adversarial Networks (GANs) have achieved state-of-the-art performance for several image generation and manipulation tasks.
MeliusNet: Can Binary Neural Networks Achieve MobileNet-level Accuracy?
However, the binarization of weights and activations leads to feature maps of lower quality and lower capacity and thus a drop in accuracy compared to traditional networks.
KISS: Keeping It Simple for Scene Text Recognition
Most of these methods propose novel building blocks for neural networks.
Back to Simplicity: How to Train Accurate BNNs from Scratch?
Binary Neural Networks (BNNs) show promising progress in reducing computational and memory costs but suffer from substantial accuracy degradation compared to their real-valued counterparts on large-scale datasets, e. g., ImageNet.
Training Competitive Binary Neural Networks from Scratch
In our work, we focus on increasing the performance of binary neural networks without such prior knowledge and a much simpler training strategy.
LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks
Our student (localizer) is a model that learns to localize an object, the teacher (assessor) assesses the quality of the localization and provides feedback to the student.
Learning to Train a Binary Neural Network
In our work, we focus on increasing our understanding of the training process and making it accessible to everyone.
