53 citations · 232 across the 44 of their papers we have counts for
11 papers · 1 filter
Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention
Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma
Binaural audio gives the listener an immersive experience and can enhance augmented and virtual reality. However, recording binaural audio requires specialized setup with a dummy h…
JEDAI: A System for Skill-Aligned Explainable Robot Planning
Naman Shah, Pulkit Verma, Trevor Angle +1
This paper presents JEDAI, an AI system designed for outreach and educational efforts aimed at non-AI experts. JEDAI features a novel synthesis of research ideas from integrated ta…
Joint Communication and Motion Planning for Cobots
Mehdi Dadvar, Keyvan Majd, Elena Oikonomou +2
The increasing deployment of robots in co-working scenarios with humans has revealed complex safety and efficiency challenges in the computation robot behavior. Movement among huma…
Learning Causal Models of Autonomous Agents using Interventions
Pulkit Verma, Siddharth Srivastava
One of the several obstacles in the widespread use of AI systems is the lack of requirements of interpretability that can enable a layperson to ensure the safe and reliable behavio…
Depth Infused Binaural Audio Generation using Hierarchical Cross-Modal Attention
Kranti Kumar Parida, Siddharth Srivastava, Neeraj Matiyali +1
Binaural audio gives the listener the feeling of being in the recording place and enhances the immersive experience if coupled with AR/VR. But the problem with binaural audio recor…
An Anytime Hierarchical Approach for Stochastic Task and Motion Planning
Naman Shah, Siddharth Srivastava
In order to solve complex, long-horizon tasks, intelligent robots need to carry out high-level, abstract planning and reasoning in conjunction with motion planning. However, abstra…
Discovering User-Interpretable Capabilities of Black-Box Planning Agents
Pulkit Verma, Shashank Rao Marpally, Siddharth Srivastava
Several approaches have been developed for answering users' specific questions about AI behavior and for assessing their core functionality in terms of primitive executable actions…
Planning for Proactive Assistance in Environments with Partial Observability
Anagha Kulkarni, Siddharth Srivastava, Subbarao Kambhampati
This paper addresses the problem of synthesizing the behavior of an AI agent that provides proactive task assistance to a human in settings like factory floors where they may coexi…
Beyond Image to Depth: Improving Depth Prediction using Echoes
Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma
We address the problem of estimating depth with multi modal audio visual data. Inspired by the ability of animals, such as bats and dolphins, to infer distance of objects with echo…
Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
Siddharth Srivastava, Gaurav Sharma
We propose simple yet effective improvements in point representations and local neighborhood graph construction within the general framework of graph neural networks (GNNs) for 3D…
Bandgap optimization in combinatorial graphs with tailored ground states: Application in Quantum annealing
Siddhartha Srivastava, Veera Sundararaghavan
A mixed-integer linear programming (MILP) formulation is presented for parameter estimation of the Potts model. Two algorithms are developed; the first method estimates the paramet…