7 citations · 10 across the 4 of their papers we have counts for
4 papers
Towards Latent Masked Image Modeling for Self-Supervised Visual Representation Learning
Yibing Wei, Abhinav Gupta, Pedro Morgado
Masked Image Modeling (MIM) has emerged as a promising method for deriving visual representations from unlabeled image data by predicting missing pixels from masked portions of ima…
Evaluating Continual Learning on a Home Robot
Sam Powers, Abhinav Gupta, Chris Paxton
Robots in home environments need to be able to learn new skills continuously as data becomes available, becoming ever more capable over time while using as little real-world data a…
The Challenges of Continuous Self-Supervised Learning
Senthil Purushwalkam, Pedro Morgado, Abhinav Gupta
Self-supervised learning (SSL) aims to eliminate one of the major bottlenecks in representation learning - the need for human annotations. As a result, SSL holds the promise to lea…
No RL, No Simulation: Learning to Navigate without Navigating
Meera Hahn, Devendra Chaplot, Shubham Tulsiani +3
Most prior methods for learning navigation policies require access to simulation environments, as they need online policy interaction and rely on ground-truth maps for rewards. How…