130 citations · 301 across the 12 of their papers we have counts for
13 papers
OVRL-V2: A simple state-of-art baseline for ImageNav and ObjectNav
Karmesh Yadav, Arjun Majumdar, Ram Ramrakhya +5
We present a single neural network architecture composed of task-agnostic components (ViTs, convolutions, and LSTMs) that achieves state-of-art results on both the ImageNav ("go to…
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
Arjun Majumdar, Karmesh Yadav, Sergio Arnaud +12
We present the largest and most comprehensive empirical study of pre-trained visual representations (PVRs) or visual 'foundation models' for Embodied AI. First, we curate CortexBen…
Retrospectives on the Embodied AI Workshop
Matt Deitke, Dhruv Batra, Yonatan Bisk +36
We present a retrospective on the state of Embodied AI research. Our analysis focuses on 13 challenges presented at the Embodied AI Workshop at CVPR. These challenges are grouped i…
Is Mapping Necessary for Realistic PointGoal Navigation?
Ruslan Partsey, Erik Wijmans, Naoki Yokoyama +3
Can an autonomous agent navigate in a new environment without building an explicit map? For the task of PointGoal navigation ('Go to , ') under idealized settings (no RGB-D…
Offline Visual Representation Learning for Embodied Navigation
Karmesh Yadav, Ram Ramrakhya, Arjun Majumdar +5
How should we learn visual representations for embodied agents that must see and move? The status quo is tabula rasa in vivo, i.e. learning visual representations from scratch whil…
Waypoint Models for Instruction-guided Navigation in Continuous Environments
Jacob Krantz, Aaron Gokaslan, Dhruv Batra +2
Little inquiry has explicitly addressed the role of action spaces in language-guided visual navigation -- either in terms of its effect on navigation success or the efficiency with…
Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI
Santhosh K. Ramakrishnan, Aaron Gokaslan, Erik Wijmans +10
We present the Habitat-Matterport 3D (HM3D) dataset. HM3D is a large-scale dataset of 1,000 building-scale 3D reconstructions from a diverse set of real-world locations. Each scene…
Habitat 2.0: Training Home Assistants to Rearrange their Habitat
Andrew Szot, Alex Clegg, Eric Undersander +18
We introduce Habitat 2.0 (H2.0), a simulation platform for training virtual robots in interactive 3D environments and complex physics-enabled scenarios. We make comprehensive contr…
Memory-Augmented Reinforcement Learning for Image-Goal Navigation
Lina Mezghani, Sainbayar Sukhbaatar, Thibaut Lavril +4
In this work, we present a memory-augmented approach for image-goal navigation. Earlier attempts, including RL-based and SLAM-based approaches have either shown poor generalization…
Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents
Samyak Datta, Oleksandr Maksymets, Judy Hoffman +3
Recent work has presented embodied agents that can navigate to point-goal targets in novel indoor environments with near-perfect accuracy. However, these agents are equipped with i…
ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects
Dhruv Batra, Aaron Gokaslan, Aniruddha Kembhavi +5
We revisit the problem of Object-Goal Navigation (ObjectNav). In its simplest form, ObjectNav is defined as the task of navigating to an object, specified by its label, in an unexp…
Embodied Question Answering in Photorealistic Environments with Point Cloud Perception
Erik Wijmans, Samyak Datta, Oleksandr Maksymets +6
To help bridge the gap between internet vision-style problems and the goal of vision for embodied perception we instantiate a large-scale navigation task -- Embodied Question Answe…
Habitat: A Platform for Embodied AI Research
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets +9
We present Habitat, a platform for research in embodied artificial intelligence (AI). Habitat enables training embodied agents (virtual robots) in highly efficient photorealistic 3…