18 citations · 46 across the 13 of their papers we have counts for
16 papers
Stochastic Action Prediction for Imitation Learning
Sagar Gubbi Venkatesh, Nihesh Rathod, Shishir Kolathaya +1
Imitation learning is a data-driven approach to acquiring skills that relies on expert demonstrations to learn a policy that maps observations to actions. When performing demonstra…
Scene Text Detection for Augmented Reality -- Character Bigram Approach to reduce False Positive Rate
Sagar Gubbi, Bharadwaj Amrutur
Natural scene text detection is an important aspect of scene understanding and could be a useful tool in building engaging augmented reality applications. In this work, we address…
Multi-Instance Aware Localization for End-to-End Imitation Learning
Sagar Gubbi Venkatesh, Raviteja Upadrashta, Shishir Kolathaya +1
Existing architectures for imitation learning using image-to-action policy networks perform poorly when presented with an input image containing multiple instances of the object of…
Imitation Learning for High Precision Peg-in-Hole Tasks
Sagar Gubbi, Shishir Kolathaya, Bharadwaj Amrutur
Industrial robot manipulators are not able to match the precision and speed with which humans are able to execute contact rich tasks even to this day. Therefore, as a means overcom…
One-Shot Object Localization Using Learnt Visual Cues via Siamese Networks
Sagar Gubbi Venkatesh, Bharadwaj Amrutur
A robot that can operate in novel and unstructured environments must be capable of recognizing new, previously unseen, objects. In this work, a visual cue is used to specify a nove…
Teaching Robots Novel Objects by Pointing at Them
Sagar Gubbi Venkatesh, Raviteja Upadrashta, Shishir Kolathaya +1
Robots that must operate in novel environments and collaborate with humans must be capable of acquiring new knowledge from human experts during operation. We propose teaching a rob…