167 citations · 777 across the 43 of their papers we have counts for
11 papers · 2 filters
One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment
Vinit Sarode, Xueqian Li, Hunter Goforth +5
PointNet has recently emerged as a popular representation for unstructured point cloud data, allowing application of deep learning to tasks such as object detection, segmentation a…
Argoverse: 3D Tracking and Forecasting with Rich Maps
Ming-Fang Chang, John Lambert, Patsorn Sangkloy +8
We present Argoverse -- two datasets designed to support autonomous vehicle machine learning tasks such as 3D tracking and motion forecasting. Argoverse was collected by a fleet of…
Distill Knowledge from NRSfM for Weakly Supervised 3D Pose Learning
Chaoyang Wang, Chen Kong, Simon Lucey
We propose to learn a 3D pose estimator by distilling knowledge from Non-Rigid Structure from Motion (NRSfM). Our method uses solely 2D landmark annotations. No 3D data, multi-view…
Deep Non-Rigid Structure from Motion
Chen Kong, Simon Lucey
Current non-rigid structure from motion (NRSfM) algorithms are mainly limited with respect to: (i) the number of images, and (ii) the type of shape variability they can handle. Thi…
PCRNet: Point Cloud Registration Network using PointNet Encoding
Vinit Sarode, Xueqian Li, Hunter Goforth +4
PointNet has recently emerged as a popular representation for unstructured point cloud data, allowing application of deep learning to tasks such as object detection, segmentation a…
Deep Non-Rigid Structure from Motion with Missing Data
Chen Kong, Simon Lucey
Non-Rigid Structure from Motion (NRSfM) refers to the problem of reconstructing cameras and the 3D point cloud of a non-rigid object from an ensemble of images with 2D corresponden…