Interactive object understanding, or what we can do to objects and how is a long-standing
goal of computer vision. In this paper, we tackle this problem through observation of human …

Self-driving cars must detect vehicles, pedestrians, and other traffic participants accurately to
operate safely. Small, far-away, or highly occluded objects are particularly challenging …

There exist several datasets for developing self-driving car methodologies. Manually
collected datasets impose inherent limitations on the variability of test cases and it is …

We present a system that automatically brings street view imagery to life by populating it with
naturally behaving, animated pedestrians and vehicles. Our approach is to remove existing …

The evolution of autonomous vehicles is advancing rapidly, promising a radical shift in our
future mobility. The cornerstone of building a reliable autonomous vehicle hinges on …

Recently there has been an increase in the number of available autonomous vehicle (AV)
models. To evaluate and compare the safety of the various models the AVs need to be …

The diversity and scale of annotated real-world 3D datasets limit the performance of
monocular 3D detectors. Although data augmentation holds potential, creating realistic …

Interactive object understanding, or what we can do to objects and how, is a long-standing
goal of computer vision. However, the inherent ambiguity of this task makes it difficult to …