24 citations · 50 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation
Abhinav Moudgil, Arjun Majumdar, Harsh Agrawal +2
Natural language instructions for visual navigation often use scene descriptions (e.g., "bedroom") and object references (e.g., "green chairs") to provide a breadcrumb trail to a g…
Sim-to-Real Transfer for Vision-and-Language Navigation
Peter Anderson, Ayush Shrivastava, Joanne Truong +4
We study the challenging problem of releasing a robot in a previously unseen environment, and having it follow unconstrained natural language navigation instructions. Recent work o…
Improving Vision-and-Language Navigation with Image-Text Pairs from the Web
Arjun Majumdar, Ayush Shrivastava, Stefan Lee +3
Following a navigation instruction such as 'Walk down the stairs and stop at the brown sofa' requires embodied AI agents to ground scene elements referenced via language (e.g. 'sta…
Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environments
Jacob Krantz, Erik Wijmans, Arjun Majumdar +2
We develop a language-guided navigation task set in a continuous 3D environment where agents must execute low-level actions to follow natural language navigation directions. By bei…
Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning
David Mascharka, Philip Tran, Ryan Soklaski +1
Visual question answering requires high-order reasoning about an image, which is a fundamental capability needed by machine systems to follow complex directives. Recently, modular…