Roboflow 100: A New Object Detection Benchmark

Advancing the state-of-the-art in object recognition with a new way to benchmark computer vision models across domains and task targets. Introduced November 2022, presented at CVPR in June 2023.

What is the Roboflow 100?

Roboflow 100 introduces domain-specific benchmarks beyond common objects in context to identify how models adapt to diverse problems in healthcare, aerial imagery, video games, and more.

Object detection benchmarks have traditionally focused on a single dataset for fine-tuning and evaluation such as Microsoft COCO and Pascal VOC. While semantically diverse within their domain, these benchmarks focus on optimizing a single metric for a single dataset, which does not show the degree of generalization learned by the model.

In this paper we introduce the Roboflow 100 object detection benchmark consisting of 100 projects that span a wide array of imagery domains and task targets. We derived our benchmark selection from over 90000 public datasets, 60 million public images that are actively being worked on in the open on Roboflow.

100
Separate datasets
7
Imagery domains
224,714
Images
829
Class labels
11,170
Labeling hours

Inspired by

The assembly of the Roboflow 100 benchmark was inspired by the research community naturally using Roboflow datasets to test model generalizability in Microsoft's Florence and GLIP.

How to use

Details can be found on the Roboflow 100 GitHub page.

Organizers

Floriana Ciaglia, Francesco Saverio Zuppichini, Paul Guerrie, Mark McQuade, and Jacob Solawetz

Made by

The Roboflow Community

Sponsored by

Intel