CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving

TL;DR

CODA is a new challenging dataset of real-world driving scenes with corner cases, revealing the limitations of current object detectors and highlighting the need for more robust autonomous vehicle perception systems.

Contribution

We introduce CODA, a novel dataset with 1500 real-world scenes containing diverse corner cases to evaluate and improve autonomous driving object detection.

Findings

Standard detectors perform poorly on CODA, with mAR below 12.8%.

State-of-the-art open-world detectors also fail on corner cases.

CODA exposes critical gaps in current autonomous vehicle perception methods.

Abstract

Contemporary deep-learning object detection methods for autonomous driving usually assume prefixed categories of common traffic participants, such as pedestrians and cars. Most existing detectors are unable to detect uncommon objects and corner cases (e.g., a dog crossing a street), which may lead to severe accidents in some situations, making the timeline for the real-world application of reliable autonomous driving uncertain. One main reason that impedes the development of truly reliably self-driving systems is the lack of public datasets for evaluating the performance of object detectors on corner cases. Hence, we introduce a challenging dataset named CODA that exposes this critical problem of vision-based detectors. The dataset consists of 1500 carefully selected real-world driving scenes, each containing four object-level corner cases (on average), spanning more than 30 object categories. On CODA, the performance of standard object detectors trained on large-scale autonomous driving datasets significantly drops to no more than 12.8% in mAR. Moreover, we experiment with the state-of-the-art open-world object detector and find that it also fails to reliably identify the novel objects in CODA, suggesting that a robust perception system for autonomous driving is probably still far from reach. We expect our CODA dataset to facilitate further research in reliable detection for real-world autonomous driving. Our dataset will be released at https://coda-dataset.github.io.