If your team are interested in attending our challenge, please fill out this registration form: https://www.wjx.cn/vj/Om0PuoM.aspx.

The link to the challenge page is: https://workshopcv.github.io/challenge.html.

News

2021/07/20: Workshop details is available.

2021/07/08: The workshop proposal is accepted.

Overview

Currently, many visual task algorithms are developed on clear image or video data with high quality. However, in the practical applications, the changing weather conditions (e.g., rain or fog) and illumination conditions (e.g., nighttime) lead to fast degradation of those algorithms. Taking the light condition for example, early research focused on high-quality image or daytime scenes with better illumination. Existing vision techniques have achieved better results with an approximately accuracy rate of 96% with these conditions. In practice, nearly 90% of criminal activities occur in the night scenes with low quality, especially in major cases. The video data collected by the surveillance system in these scene has low contrast and poor quality. According to the Ministry of Public Security Evidence Identification Center (China), the proportion of poor quality video images at night is as high as 95%, and the performance of current methods on low- quality visible images is low, which is difficult to cope with the actual security needs. There is an urgent need to optimize this problem.

In this workshop, we prepared a grand challenge on under low illumination, as well as call for papers about vision tasks under general adverse weather. Please find the details below:

Challenge

The goal of this challenges to:

1. Bring together the state of the art research on object detection under low illumination;
2. Call for a coordinated effort to understand the opportunities and challenges emerging in object detection;
3. Identify key tasks and evaluate the state-of-the-art methods;
4. Showcase innovative methodologies and ideas;
5. Introduce interesting real-world intelligent object detection under low illumination;
6. Propose new real-world datasets and discuss future directions. We believe the workshop will offer a timely collection of research updates to benefit the researchers and practitioners working in the broad computer vision, multimedia, and pattern recognition communities.

Call for Papers

Except for the challenge, we solicit original research and survey papers in (but not limited to) the following topics:

• Pedestrian detection in low illumination, low resolution, rain and fog, etc.
• Object detection in low illumination, low resolution, rain and fog, etc.
• Person re-identification in low illumination, low resolution, rain and fog, etc.
• Object recognition in low illumination, low resolution, rain and fog, etc.
• Segmentation in low illumination, low resolution, rain and fog, etc.
• Counting in low illumination, low resolution, rain and fog, etc.

Important Dates

Organizers