3 accepted papers
Recently, the community has witnessed significant progress in human modeling from single or multi-view inputs. However, these approaches often rely on guessing the occluded regions through either generative models or template fitting. In this work, we address these challenges by exploring optimal fu
A well-known challenge in applying deep-learning methods to omnidirectional images is spherical distortion. In dense regression tasks such as depth estimation, where structural details are required, using a vanilla CNN layer on the distorted 360 image results in undesired information loss. In this p…
This paper presents a new deep learning architecture called PointGrid that is designed for 3D model recognition from unorganized point clouds. The new architecture embeds the input point cloud into a 3D grid by a simple, yet effective, sampling strategy and directly learns transformations and featur…