no code implementations • CVPR 2014 • Santosh K. Divvala, Ali Farhadi, Carlos Guestrin
How can we learn a model for any concept that exhaustively covers all its appearance variations, while requiring minimal or no human supervision for compiling the vocabulary of visual variance, gathering the training images and annotations, and learning the models?
