The first Workshop on Computer Vision for Global Challenges will be held in conjunction with the IEEE Coference on Computer Vision and Pattern Recognition (CVPR), in Long Beach, California on June 16th 2019. It will be a full-day event and will feature invited speakers, poster and spotlight presentations, a panel discussion and a mentoring/networking dinner.
Our goal is to widen the scope of current computer vision technology, to include novel problems, data and applications of world-wide impact. Our visual world is diverse, and so should our technology be.
If you don’t have a concrete idea or results, but you’d like to get involved, here are some amazing volunteer opportunities:
Recipients of accepted proposals may receive full travel grants (transportation, accommodation, registration and meals) to attend the CVPR conference, tutorials and workshops. The review process is single-blind and immigration letters will be provided.
Researchers or practitioners based in developing regions are strongly encouraged to apply.
Travel grants and US Visa: Keeping in mind how time-consuming the Visa processes can be, we expect to announce decisions for applicants that do not have a US Visa around mid-April. This will hopefully allow enough time for the visa process to finish on time.
The submission deadline for the Call for Challenges is March 25th, 2019.
Please note that, while there’s a wider range of work under the social good umbrella, we are particularly interested in works applied to and challenges coming from developing regions.
Submissions will be handled via CMT: https://cmt3.research.microsoft.com/CV4GC2019
The paper submission deadline is March 31st, 2019.
Deadline to apply is April 29.
Taking a global perspective on computer vision, also means widening participation. We will bring people who come to CVPR for the first time, which can be overwhelming (you probably still remember your first CVPR). We want these people to make the most of it, be prepared to showcase their material etc. We are therefore accepting volunteers from the CV community, that would act as "vision ambassadors" for each newcomer that needs help.
If accepted, you will be the mentor of a CVPR newcomer, and you are expected to connect with them before the conference, answer questions via email or video conferencing, assist them with their presentation and poster printing in needed. During the conference, you will help the newcomer orient, socialize and connect to the right people. We require that you have attended at least 2 top-tier Computer Vision conferences (CVPR/ICCV/ECCV) during the last couple of years to qualify.
If you are interested in being a computer vision ambassador please fill out the volunteer form.
Computer vision technology has recently made rapid progress in several subareas (e.g., object segmentation, video classification), achieving a level of performance that was unexpected just a few years ago. This technology has opened possibilities in many real world domains including transportation (self-driving cars, drones), entertainment (shopping, phones), safety (security systems), which are used on a daily basis to make our lives more efficient, richer, and safer. While these applications give meaning and value to our technology, their focus on certain geographical regions or markets, often in first world countries, injects biases in our datasets, tasks, and ultimately direction of the progress of the field.
Parallel to this, penetration of internet and mobile device usage in developing countries has largely increased in the past years; more people today have access to mobile phones than to piped water supply. Access to network connected computing devices which often have a camera offers computer vision a unique opportunity to bypass the lack of infrastructure and deliver expertise, advice, or information to those in need. Examples of such applications are be in farming, health care, or clean water, among others. These applications, however, often pose challenges that are not necessarily addressed in existing computer vision practices sufficiently. Dealing with datasets with a diversity matching that of the real world, addressing problems falling in the long tail distribution of data availability, or reduction of biases towards certain classes/tasks/ethnicities are some of those challenges, just to name a few. Thus, widening the scope of computer vision to address such problems could lead to a two way advantage: vision could positively impact the lives of 6 billion people in developing regions, and that could reveal some of the blind spots and biases in our current computer vision datasets, tasks, practices, and ultimately lead to purely technical progress.
Why has this opportunity not been seized before? We argue that one of the main obstacles is the disconnection between domain experts: those who know about the problems, and those who know about technical solutions. This disconnection may be geographical, may be of language, and may even be due to lack of a forum to find each other. We propose this initiative with the purpose of bridging the gap between these two communities. In particular our goals are: