16 citations · 42 across the 6 of their papers we have counts for
9 papers
Correspondence Matrices are Underrated
Tejas Zodage, Rahul Chakwate, Vinit Sarode +2
Point-cloud registration (PCR) is an important task in various applications such as robotic manipulation, augmented and virtual reality, SLAM, etc. PCR is an optimization problem i…
MaskNet: A Fully-Convolutional Network to Estimate Inlier Points
Vinit Sarode, Animesh Dhagat, Rangaprasad Arun Srivatsan +3
Point clouds have grown in importance in the way computers perceive the world. From LIDAR sensors in autonomous cars and drones to the time of flight and stereo vision systems in o…
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…
Globally optimal registration of noisy point clouds
Rangaprasad Arun Srivatsan, Tejas Zodage, Howie Choset
Registration of 3D point clouds is a fundamental task in several applications of robotics and computer vision. While registration methods such as iterative closest point and varian…
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…
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
Yasuhiro Aoki, Hunter Goforth, Rangaprasad Arun Srivatsan +1
PointNet has revolutionized how we think about representing point clouds. For classification and segmentation tasks, the approach and its subsequent extensions are state-of-the-art…