no code implementations • 11 Feb 2024 • Atharva Pandey, Vishal Yadav, Rajendra Nagar, Santanu Chaudhury
We then propose a neural network architecture for learning the linear implicit shape representation of the 3D surface of an object.
no code implementations • 21 Sep 2021 • Rajendra Nagar
In this work, we proposed a statistical estimator-based approach for the plane of reflection symmetry that is robust to outliers and missing parts.
1 code implementation • 27 Jul 2021 • Abhinav Narayan Harish, Rajendra Nagar, Shanmuganathan Raman
Autonomous assembly of objects is an essential task in robotics and 3D computer vision.
no code implementations • ECCV 2018 • Rajendra Nagar, Shanmuganathan Raman
In this work, we detect the intrinsic reflective symmetry in triangle meshes where we have to find the intrinsically symmetric point for each point of the shape.
no code implementations • 23 May 2018 • Rajendra Nagar, Shanmuganathan Raman
We partition the image into superpixels while preserving this reflection symmetry through an iterative algorithm.
no code implementations • 27 Jun 2017 • Rajendra Nagar, Shanmuganathan Raman
We formulate an optimization framework in which the problem of establishing the correspondences amounts to solving a linear assignment problem and the problem of determining the reflection symmetry transformation amounts to solving an optimization problem on a smooth Riemannian product manifold.