30th April 2018 new version of Open Images Dataset V4 is released. There is also announced a challenge for best object detection results using this dataset.
Here you can see data examples: Open Images Dataset V4
ECCV 2018 Open Images Challenge
During ECCV 2018 conference there will be a workshop dedicated Open Images Challenge (presented by Vittorio Ferrari, Alina Kuznetsova, Jasper Uijlings, Rodrigo Benenson, Victor Gomes, Matteo Malloci). They will announce challenge results.
The Challenge has two tracks:
- Object Class Detection: predicting a tight bounding box around all instances of the 500 classes.
- Visual Relationship Detection: detecting pairs of objects in particular relations, e.g. “woman playing guitar”.
There are image-level labels (table 1) and bounding boxes for object detection (table 2). Labels where generated automatically by machine and then checked by humans thanks to Crowdsource labeler.
Table 1: Image-level labels
|Train||Validation||Test||# Classes||# Trainable Classes|
Table 2: Object Detection track annotations on training set
|Classes||Images||Image-Level Labels||Bounding boxes|
Here are some examples, more you can find here: Open Images Dataset V4
- April 30th 2018: training set for object detection track released (with bounding box annotations).
- May 10 2018: visual relationship detection annotations on the training set will be released.
- May 31 2018: evaluation metric protocols and implementation will be released (as a part of the TF Object Detection API).
- July 1st 2018: a test set of 100k images will be released by Kaggle.
- September 1st 2018: deadline for submission of results.
- September 8th 2018: Open Images Challenge Workshop