Abhinav Gupta

Abhinav is a Research Manager at Facebook AI Research (FAIR), and Associate Professor at CMU. His research focuses on scaling up learning by building self-supervised, lifelong, and interactive learning systems. He is examining how self-supervised systems can effectively use data to learn visual representation, common sense, and representation for actions in robots. Abhinav is a recipient of numerous awards including ONR Young Investigator Award, PAMI Young Researcher Award, Sloan Research Fellowship, Okawa Foundation Grant, Bosch Young Faculty Fellowship, YPO Fellowship, IJCAI Early Career Spotlight, ICRA Best Student Paper Award, and the ECCV Best Paper Runner-up Award.

Abhinav's Publications



Object-centric Forward Modeling for Model Predictive Control

We present an approach to learn an object-centric forward model, and show that this allows us to plan for sequences of actions to achieve distant desired goals. We propose to model a scene as a collection of objects, each with an explicit…

Yufei Ye, Dhiraj Gandhi, Abhinav Gupta, Shubham Tulsiani



Task-Driven Modular Networks for Zero-Shot Compositional Learning

One of the hallmarks of human intelligence is the ability to compose learned knowledge into novel concepts which can be recognized without a single training example. In contrast, current state-of-the-art methods require hundreds of training…

Senthil Purushwalkam, Maximilian Nickel, Abhinav Gupta, Marc'Aurelio Ranzato


Canonical Surface Mapping via Geometric Cycle Consistency

We explore the task of Canonical Surface Mapping (CSM). Specifically, given an image, we learn to map pixels on the object to their corresponding locations on an abstract 3D model of the category. But how do we learn such a mapping? A…

Nilesh Kulkarni, Abhinav Gupta, Shubham Tulsiani