Learning 10,000 Visual Classes and Some Stuff

The goal of this project is to solve some of the most fundamental yet challenging problems in computer vision - object detection, localisation and recognition in large-scale.

With the development of hardware, people nowadays have much more images in the size of G bytes than before. In the light of this, the research in the direction of processing big data attracts wide public attention.

Due to large-scale visual object categories, the inter-class variation and computational complexity will further increase the difficulties in addition to large intra-class variation.

The main focus of this project is set to improve the accuracy and efficiency of the-state-of-arts for large-scale visual object recognition.

The project is mainly carried out using the funding from Academy of Finland.

People

Publications

Dataset

ImageNet

ILSVRC

Research Group

Supervision

VGG