liuzhuang13/DenseNet

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

4869 stars · 1063 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Reference implementation of DenseNet (Densely Connected Convolutional Networks), the CVPR 2017 Best Paper Award-winning CNN architecture, written in Lua on the Torch framework. It includes a memory-efficient implementation and links to community ports in PyTorch, TensorFlow, Keras, and other frameworks.

Use cases

• train a DenseNet image classification model
• reproduce the CVPR 2017 DenseNet paper results
• study densely connected convolutional network architecture code
• get a memory-efficient DenseNet implementation
• classify images with a densely connected CNN

When to choose

• you need the original reference implementation of DenseNet
• you are doing research on or reproducing the DenseNet paper
• you specifically work with the Torch (Lua) deep learning stack

When to avoid

• you want to use DenseNet in production with modern tooling - use torchvision or Keras implementations instead
• you do not use the legacy Torch/Lua framework
• you need actively maintained code with recent updates and support

Facets

library · maturity abandoned

deep-learning machine-learning image-processing computer-vision deep-learning computer-vision machine-learning image-processing lua densenet convolutional-networks torch research-code cvpr-2017 image-classification gpu linux

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