10 citations · 18 across the 8 of their papers we have counts for
9 papers
AnyLoc: Towards Universal Visual Place Recognition
Nikhil Keetha, Avneesh Mishra, Jay Karhade +4
Visual Place Recognition (VPR) is vital for robot localization. To date, the most performant VPR approaches are environment- and task-specific: while they exhibit strong performanc…
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…
Sequence-Agnostic Multi-Object Navigation
Nandiraju Gireesh, Ayush Agrawal, Ahana Datta +4
The Multi-Object Navigation (MultiON) task requires a robot to localize an instance (each) of multiple object classes. It is a fundamental task for an assistive robot in a home or…
ConceptFusion: Open-set Multimodal 3D Mapping
Krishna Murthy Jatavallabhula, Alihusein Kuwajerwala, Qiao Gu +14
Building 3D maps of the environment is central to robot navigation, planning, and interaction with objects in a scene. Most existing approaches that integrate semantic concepts wit…
SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping
Bipasha Sen, Aditya Agarwal, Gaurav Singh +3
Recovering full 3D shapes from partial observations is a challenging task that has been extensively addressed in the computer vision community. Many deep learning methods tackle th…
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields
Rohith Agaram, Shaurya Dewan, Rahul Sajnani +3
Coordinate-based implicit neural networks, or neural fields, have emerged as useful representations of shape and appearance in 3D computer vision. Despite advances, however, it rem…
Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation
D. A. Sasi Kiran, Kritika Anand, Chaitanya Kharyal +7
This paper describes a framework for the object-goal navigation task, which requires a robot to find and move to the closest instance of a target object class from a random startin…
Object Goal Navigation using Data Regularized Q-Learning
Nandiraju Gireesh, D. A. Sasi Kiran, Snehasis Banerjee +3
Object Goal Navigation requires a robot to find and navigate to an instance of a target object class in a previously unseen environment. Our framework incrementally builds a semant…
MergeNet: A Deep Net Architecture for Small Obstacle Discovery
Krishnam Gupta, Syed Ashar Javed, Vineet Gandhi +1
We present here, a novel network architecture called MergeNet for discovering small obstacles for on-road scenes in the context of autonomous driving. The basis of the architecture…