Object detection is of significant value to the Computer Vision and Pattern Recognition communities as it is one of the fundamental vision problems. In this workshop, we will introduce two new benchmarks for the object detection task: Objects365 and CrowdHuman, both of which are designed and collected in the wild. Objects365 benchmark targets to address the large-scale detection with 365 object categories. There will be two tracks: full track with all of 365 object categories on the 600K training images and tiny track to address the 100 challenging categories on sub-set of the training images. CrowdHuman, on the other hand, is targeting the problem of human detection in the crowd. We hope these two datasets can provide the diverse and practical benchmarks to advance the research of object detection. Also, this workshop can serve as a platform to push the upper-bound of object detection research.
[News] The workshop website is now online.
|Challenge Launch Date||April 16, 2019|
|Testing Data Release||May 10, 2019|
|Result Submissions Deadline||June 12, 2019|
|Workshop date||June 17, 2019|
The Objects365 is a brand new dataset, designed to spur object detection research with a focus on diverse objects in the Wild. Objects365 has 365 object classes annotated on 638K images, totally with more than 10 million bounding boxes in the training set. Thus the annotations cover common objects occurring in all kinds of scene categories. Challenge for Objects365 is proposed to have two tracks:
The CrowdHuman dataset is large, rich-annotated and contains high diversity. It contains 15000, 4370 and 5000 images for training, validation, and testing, respectively. There are a total of 340K human instances and 22.6 persons per image from the train set, with various kinds of occlusions in the dataset. Each human instance is annotated with a head bounding-box, human visible-region bounding-box and human full-body bounding-box. We believe this dataset will serve as a solid baseline and help promote future research in human detection tasks, especially in the crowded environment.
Contact us at firstname.lastname@example.org.