ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes

1 code implementation • 19 Jan 2022 • Rahul Sajnani, Adrien Poulenard, Jivitesh Jain, Radhika Dua, Leonidas J. Guibas, Srinath Sridhar

ConDor is a self-supervised method that learns to Canonicalize the 3D orientation and position for full and partial 3D point clouds.

3D Canonicalization 3D Geometry Perception +2

DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects

1 code implementation • 25 Nov 2020 • Rahul Sajnani, AadilMehdi Sanchawala, Krishna Murthy Jatavallabhula, Srinath Sridhar, K. Madhava Krishna

We present DRACO, a method for Dense Reconstruction And Canonicalization of Object shape from one or more RGB images.

Pose Estimation Translation

BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View

no code implementations • 15 Nov 2020 • Swapnil Daga, Gokul B. Nair, Anirudha Ramesh, Rahul Sajnani, Junaid Ahmed Ansari, K. Madhava Krishna

In this paper, we present BirdSLAM, a novel simultaneous localization and mapping (SLAM) system for the challenging scenario of autonomous driving platforms equipped with only a monocular camera.

Autonomous Driving Object Localization +1

Multi-object Monocular SLAM for Dynamic Environments

no code implementations • 10 Feb 2020 • Gokul B. Nair, Swapnil Daga, Rahul Sajnani, Anirudha Ramesh, Junaid Ahmed Ansari, Krishna Murthy Jatavallabhula, K. Madhava Krishna

In this paper, we tackle the problem of multibody SLAM from a monocular camera.