1 code implementation • 10 Aug 2023 • Alaa Maalouf, Ninad Jadhav, Krishna Murthy Jatavallabhula, Makram Chahine, Daniel M. Vogt, Robert J. Wood, Antonio Torralba, Daniela Rus
We demonstrate FAn on a real-world robotic system (a micro aerial vehicle) and report its ability to seamlessly follow the objects of interest in a real-time control loop.
1 code implementation • 1 Aug 2023 • Nikhil Keetha, Avneesh Mishra, Jay Karhade, Krishna Murthy Jatavallabhula, Sebastian Scherer, Madhava Krishna, Sourav Garg
In this work, we develop a universal solution to VPR -- a technique that works across a broad range of structured and unstructured environments (urban, outdoors, indoors, aerial, underwater, and subterranean environments) without any re-training or fine-tuning.
Ranked #1 on
Visual Place Recognition
on Nardo-Air R
no code implementations • CVPR 2023 • Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula, Daniel Cremers
We propose a differentiable nonlinear least squares framework to account for uncertainty in relative pose estimation from feature correspondences.
no code implementations • 9 Mar 2023 • Xuan Li, Yi-Ling Qiao, Peter Yichen Chen, Krishna Murthy Jatavallabhula, Ming Lin, Chenfanfu Jiang, Chuang Gan
In this work, we aim to identify parameters characterizing a physical system from a set of multi-view videos without any assumption on object geometry or topology.
no code implementations • 14 Feb 2023 • Krishna Murthy Jatavallabhula, Alihusein Kuwajerwala, Qiao Gu, Mohd Omama, Tao Chen, Shuang Li, Ganesh Iyer, Soroush Saryazdi, Nikhil Keetha, Ayush Tewari, Joshua B. Tenenbaum, Celso Miguel de Melo, Madhava Krishna, Liam Paull, Florian Shkurti, Antonio Torralba
ConceptFusion leverages the open-set capabilities of today's foundation models pre-trained on internet-scale data to reason about concepts across modalities such as natural language, images, and audio.
1 code implementation • 11 Jul 2022 • Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti
3D scene graphs (3DSGs) are an emerging description; unifying symbolic, topological, and metric scene representations.
no code implementations • 28 Jun 2022 • Rika Antonova, Jingyun Yang, Krishna Murthy Jatavallabhula, Jeannette Bohg
In this work, we study the challenges that differentiable simulation presents when it is not feasible to expect that a single descent reaches a global optimum, which is often a problem in contact-rich scenarios.
no code implementations • 20 Aug 2021 • Kaustubh Mani, N. Sai Shankar, Krishna Murthy Jatavallabhula, K. Madhava Krishna
Given an image or a video captured from a monocular camera, amodal layout estimation is the task of predicting semantics and occupancy in bird's eye view.
no code implementations • ICLR 2021 • Krishna Murthy Jatavallabhula, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine, Jerome Parent-Levesque, Kevin Xie, Kenny Erleben, Liam Paull, Florian Shkurti, Derek Nowrouzezahrai, Sanja Fidler
We consider the problem of estimating an object's physical properties such as mass, friction, and elasticity directly from video sequences.
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.
1 code implementation • 23 Nov 2020 • Saeid Asgari Taghanaki, Jieliang Luo, Ran Zhang, Ye Wang, Pradeep Kumar Jayaraman, Krishna Murthy Jatavallabhula
We also find that robustness to unseen transformations cannot be brought about merely by extensive data augmentation.
3 code implementations • 19 Feb 2020 • Kaustubh Mani, Swapnil Daga, Shubhika Garg, N. Sai Shankar, Krishna Murthy Jatavallabhula, K. Madhava Krishna
We dub this problem amodal scene layout estimation, which involves "hallucinating" scene layout for even parts of the world that are occluded in the image.
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.
6 code implementations • 12 Nov 2019 • Krishna Murthy Jatavallabhula, Edward Smith, Jean-Francois Lafleche, Clement Fuji Tsang, Artem Rozantsev, Wenzheng Chen, Tommy Xiang, Rev Lebaredian, Sanja Fidler
We present Kaolin, a PyTorch library aiming to accelerate 3D deep learning research.
1 code implementation • 23 Oct 2019 • Krishna Murthy Jatavallabhula, Soroush Saryazdi, Ganesh Iyer, Liam Paull
Blending representation learning approaches with simultaneous localization and mapping (SLAM) systems is an open question, because of their highly modular and complex nature.