3k citations · 5k across the 31 of their papers we have counts for
5 papers · 1 filter
Learning by Cheating
Dian Chen, Brady Zhou, Vladlen Koltun +1
Vision-based urban driving is hard. The autonomous system needs to learn to perceive the world and act in it. We show that this challenging learning problem can be simplified by de…
Monocular Plan View Networks for Autonomous Driving
Dequan Wang, Coline Devin, Qi-Zhi Cai +2
Convolutions on monocular dash cam videos capture spatial invariances in the image plane but do not explicitly reason about distances and depth. We propose a simple transformation…
Does computer vision matter for action?
Brady Zhou, Philipp Krähenbühl, Vladlen Koltun
Computer vision produces representations of scene content. Much computer vision research is predicated on the assumption that these intermediate representations are useful for acti…
Objects as Points
Xingyi Zhou, Dequan Wang, Philipp Krähenbühl
Detection identifies objects as axis-aligned boxes in an image. Most successful object detectors enumerate a nearly exhaustive list of potential object locations and classify each.…
Bottom-up Object Detection by Grouping Extreme and Center Points
Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl
With the advent of deep learning, object detection drifted from a bottom-up to a top-down recognition problem. State of the art algorithms enumerate a near-exhaustive list of objec…