Update (September 22, 2016): The Google Brain team has released the image captioning model of Vinyals et al. (2015). The core model is very similar to NeuralTalk2 (a CNN followed by RNN), but the Google release should work significantly better as a result of better CNN, some tricks, and more careful engineering. Find it under im2txt repo in tensorflow. I'll leave this code base up for educational purposes and as a Torch implementation. Recurrent Neural Network captions your images. Now much faster and better than the original NeuralTalk. Compared to the original NeuralTalk this implementation is batched, uses Torch, runs on a GPU, and supports CNN finetuning. All of these together result in quite a large increase in training speed for the Language Model (~100x), but overall not as much because we also have to forward a VGGNet. However, overall very good models can be trained in 2-3 days, and they show a much better performance.