Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …

Validation metrics are key for tracking scientific progress and bridging the current chasm
between artificial intelligence research and its translation into practice. However, increasing …

Humans can use the Internet to share knowledge and to help each other accomplish
complex tasks. Until now, robots have not taken advantage of this opportunity. Sharing …

Object detection is one of the most fundamental and challenging tasks to locate objects in
images and videos. Over the past, it has gained much attention to do more research on …

Background In the era of information overload, are big data analytics the answer to access
and better manage available knowledge? Over the last decade, the use of Web-based data …

Abstract The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object
category recognition and detection, providing the vision and machine learning communities …

We seek to build a large collection of images with ground truth labels to be used for object
detection and recognition research. Such data is useful for supervised learning and …

Recently, methods based on local image features have shown promise for texture and
object recognition tasks. This paper presents a large-scale evaluation of an approach that …

The world is long-tailed. What does this mean for computer vision and visual recognition?
The main two implications are (1) the number of categories we need to consider in …

Prior work in 3D object detection evaluates models using offline metrics like average
precision since closed-loop online evaluation on the downstream driving task is costly …