12 citations · 17 across the 2 of their papers we have counts for
5 papers
CLIPGraphs: Multimodal Graph Networks to Infer Object-Room Affinities
Ayush Agrawal, Raghav Arora, Ahana Datta +5
This paper introduces a novel method for determining the best room to place an object in, for embodied scene rearrangement. While state-of-the-art approaches rely on large language…
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares
Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula +1
We propose a differentiable nonlinear least squares framework to account for uncertainty in relative pose estimation from feature correspondences. Specifically, we introduce a symm…
PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification
Xuan Li, Yi-Ling Qiao, Peter Yichen Chen +4
Existing approaches to system identification (estimating the physical parameters of an object) from videos assume known object geometries. This precludes their applicability in a v…
TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs
Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir +5
3D scene graphs (3DSGs) are an emerging description; unifying symbolic, topological, and metric scene representations. However, typical 3DSGs contain hundreds of objects and symbol…
Rethinking Optimization with Differentiable Simulation from a Global Perspective
Rika Antonova, Jingyun Yang, Krishna Murthy Jatavallabhula +1
Differentiable simulation is a promising toolkit for fast gradient-based policy optimization and system identification. However, existing approaches to differentiable simulation ha…