1.4k citations · 3.7k across the 6 of their papers we have counts for
5 papers · 1 filter
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
Oriol Vinyals, Alexander Toshev, Samy Bengio +1
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In this paper, w…
Domain Separation Networks
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman +2
The cost of large scale data collection and annotation often makes the application of machine learning algorithms to new tasks or datasets prohibitively expensive. One approach cir…
Training Deep Neural Networks on Noisy Labels with Bootstrapping
Scott Reed, Honglak Lee, Dragomir Anguelov +3
Current state-of-the-art deep learning systems for visual object recognition and detection use purely supervised training with regularization such as dropout to avoid overfitting.…
Show and Tell: A Neural Image Caption Generator
Oriol Vinyals, Alexander Toshev, Samy Bengio +1
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In this paper, w…
Going Deeper with Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia +6
We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in th…