The 1st International Workshop on Feature and Similarity Learning for Computer Vision (FSLCV 2014) will be held in Singapore, December 2014, in conjunction with 2014 Asian Conference on Computer Vision (ACCV 2014).


Learning good feature representation and similarity is at the core of numerous computer vision applications, and a large number of such methods have been proposed over the past decade. These methods aim to learn a robust feature representation and an appropriate distance/similarity function for a given task, and they have been successfully applied in many computer vision tasks such as face and object recognition, visual tracking, human action recognition and visual search. The ambition of this workshop aims to provide an opportunity to disseminate recent theories, methods, and practical algorithms that explicitly exploit the enormous potential of feature and similarity learning for a wide variety of computer vision tasks. This workshop aims to explore recent progress in feature and similarity learning for computer vision by taking stock of the past five years of work in this field and evaluating different algorithms. This workshop will help the community to understand the challenges and opportunities of feature and similarity learning techniques and their applications in computer vision for the next few years in this area.


We are pleased to announce that the paper "Everything is in the face? Represent faces with object bank", authorized by Xin Liu, Shiguang Shan, Shaoxin Li, and Alexander G. Hauptmann, was awarded the ZTE best paper award.  Congratulations!

ZET Best Paper Award

We are happy to announce that ZTE will support the best paper award (USD 500.00)! We thank ZTE for there support!

The latest program for FSLCV'2014 can be found here:  

Prof Xudong Jiang and Prof Sinno Jialin Pan will give two talks in the workshop!