Papers are sought in the following areas:
The program committee will review papers and provide suggestions for either a poster or oral presentation. Note that scientific contribution is a must; however, we encourage preliminary approaches that partially solve a challenging issue, or solutions that target a problem of interest but are not necessarily state-of-the-art in terms of performance (e.g., a method that scales to 1 trillion images on a mobile phone, but is 2% behind the winner on the latest vision challenge so would not necessarily be considered 'state of the art'). The aim of the workshop is to look to the future, as much as it is to demonstrate successes of the (recent) past.
We especially solicit posters and/or demos from projects (e.g. internal, NSF funded, EU projects). This can be from projects near completion -- an opportunity to show the community what challenges were addressed and demonstrate and software / datasets / systems that were produced. Alternatively, these can form outlines, ideas, open problems. The idea is to raise awareness of all activities in the joint area of machine learning / computer vision among as many researchers as possible. We will aim to accommodate as many relevant demos/project posters as possible.
Our overall aim: is to promote fruitful discussion among researchers from both communities, to raise awareness of work / challenges / projects / datasets, and to provide a relaxed environment in which to discuss these aspects. We are not aiming at a processional mini-conference, the outcome of the workshop should be more than a list of papers to go and read: hopefully you will have new contacts and new research ideas to get very excited about.