Occlusions play an important role in optical flow and disparity estimation, since matching
costs are not available in occluded areas and occlusions indicate motion boundaries …

Scene flow estimation has been receiving increasing attention for 3D environment
perception. Monocular scene flow estimation-obtaining 3D structure and 3D motion from two …

We describe an approach for upgrading 2D optical flow to 3D scene flow. Our key insight is
that dense optical expansion-which can be reliably inferred from monocular frame pairs …

We introduce a compact network for holistic scene flow estimation, called SENSE, which
shares common encoder features among four closely-related tasks: optical flow estimation …

Dynamic obstacle avoidance is one crucial component for compliant navigation in crowded
environments. In this paper we present a system for accurate and reliable detection and …

The stereo matching algorithm is one of the important methods for 3D surface reconstruction.
A stereo matching process produces a disparity map which provides the depth of information …

Dense pixel matching is important for many computer vision tasks such as disparity and flow
estimation. We present a robust, unified descriptor network that considers a large context …

This report is a survey of the different autonomous driving datasets which have been
published up to date. The first section introduces the many sensor types used in …

We present a method for optimizing object-level rigid 3D scene flow over two successive
point clouds without any annotated labels in autonomous driving settings. Rather than using …

While most scene flow methods use either variational optimization or a strong rigid motion
assumption, we show for the first time that scene flow can also be estimated by dense …