44 citations · 138 across the 30 of their papers we have counts for
4 papers · 1 filter
Can generalised relative pose estimation solve sparse 3D registration?
Siddhant Ranade, Xin Yu, Shantnu Kakkar +2
Popular 3D scan registration projects, such as Stanford digital Michelangelo or KinectFusion, exploit the high-resolution sensor data for scan alignment. It is particularly challen…
Equivalent and Approximate Transformations of Deep Neural Networks
Abhinav Kumar, Thiago Serra, Srikumar Ramalingam
Two networks are equivalent if they produce the same output for any given input. In this paper, we study the possibility of transforming a deep neural network to another network wi…
Minimal Solvers for Mini-Loop Closures in 3D Multi-Scan Alignment
Pedro Miraldo, Surojit Saha, Srikumar Ramalingam
3D scan registration is a classical, yet a highly useful problem in the context of 3D sensors such as Kinect and Velodyne. While there are several existing methods, the techniques…
3DRegNet: A Deep Neural Network for 3D Point Registration
G. Dias Pais, Srikumar Ramalingam, Venu Madhav Govindu +3
We present 3DRegNet, a novel deep learning architecture for the registration of 3D scans. Given a set of 3D point correspondences, we build a deep neural network to address the fol…