85 citations · 497 across the 23 of their papers we have counts for
31 papers · 1 filter
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…
Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data
Michael Cogswell, Jiasen Lu, Rishabh Jain +3
Can we develop visually grounded dialog agents that can efficiently adapt to new tasks without forgetting how to talk to people? Such agents could leverage a larger variety of exis…
Seeing the Un-Scene: Learning Amodal Semantic Maps for Room Navigation
Medhini Narasimhan, Erik Wijmans, Xinlei Chen +4
We introduce a learning-based approach for room navigation using semantic maps. Our proposed architecture learns to predict top-down belief maps of regions that lie beyond the agen…
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…
Are we pretraining it right? Digging deeper into visio-linguistic pretraining
Amanpreet Singh, Vedanuj Goswami, Devi Parikh
Numerous recent works have proposed pretraining generic visio-linguistic representations and then finetuning them for downstream vision and language tasks. While architecture and o…
SQuINTing at VQA Models: Introspecting VQA Models with Sub-Questions
Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh +4
Existing VQA datasets contain questions with varying levels of complexity. While the majority of questions in these datasets require perception for recognizing existence, propertie…