4 citations · 13 across the 5 of their papers we have counts for
6 papers
Monocular Object Orientation Estimation using Riemannian Regression and Classification Networks
Siddharth Mahendran, Ming Yang Lu, Haider Ali +1
We consider the task of estimating the 3D orientation of an object of known category given an image of the object and a bounding box around it. Recently, CNN-based regression and c…
A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images
Siddharth Mahendran, Haider Ali, Rene Vidal
3D pose estimation from a single 2D image is an important and challenging task in computer vision with applications in autonomous driving, robot manipulation and augmented reality.…
Convolutional Networks for Object Category and 3D Pose Estimation from 2D Images
Siddharth Mahendran, Haider Ali, Rene Vidal
Current CNN-based algorithms for recovering the 3D pose of an object in an image assume knowledge about both the object category and its 2D localization in the image. In this paper…
3D Pose Regression using Convolutional Neural Networks
Siddharth Mahendran, Haider Ali, Rene Vidal
3D pose estimation is a key component of many important computer vision tasks such as autonomous navigation and 3D scene understanding. Most state-of-the-art approaches to 3D pose…
Car Segmentation and Pose Estimation using 3D Object Models
Siddharth Mahendran, René Vidal
Image segmentation and 3D pose estimation are two key cogs in any algorithm for scene understanding. However, state-of-the-art CRF-based models for image segmentation rely mostly o…
Hypothesize and Bound: A Computational Focus of Attention Mechanism for Simultaneous 3D Shape Reconstruction, Pose Estimation and Classification from a Single 2D Image
Diego Rother, Siddharth Mahendran, René Vidal
This article presents a mathematical framework to simultaneously tackle the problems of 3D reconstruction, pose estimation and object classification, from a single 2D image. In sha…