The 1st International Workshop on Visual Tasks and Challenges under Low-quality Media Data

ACM MM Asia 2021, Gold Coast, Australia, December1-3, 2021


News

2021/07/20: Workshop details is available.

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


Overview

The field of computer vision has been a research hotspot, and 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.


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. Ldentify 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

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

Challenge train dataset release August 10, 2021
Challenge validation dataset release September 10, 2021
Challenge test dataset release September 24, 2021
Challenge Result Submission Close October 8, 2021
Workshop Paper Submission October 18, 2021
Workshop Paper Notification November 1, 2021


Organizers

Jing Xiao
Wuhan University
Xiao Wang
Wuhan University
Liang Liao
National Institute of Informatics
Shin'ichi Satoh
National Institute of Informatics
Chia-Wen Lin
National Tsing Hua University