activity
20182022
most citedGraph2Vid: Flow graph to Video Grounding for Weakly-supervised Multi-Step Localization

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

Graph2Vid: Flow graph to Video Grounding for Weakly-supervised Multi-Step Localization

Nikita Dvornik, Isma Hadji, Hai Pham +4

In this work, we consider the problem of weakly-supervised multi-step localization in instructional videos. An established approach to this problem is to rely on a given list of st…

cs.CV2022

Visual Semantic Parsing: From Images to Abstract Meaning Representation

Mohamed Ashraf Abdelsalam, Zhan Shi, Federico Fancellu +4

The success of scene graphs for visual scene understanding has brought attention to the benefits of abstracting a visual input (e.g., image) into a structured representation, where…

cs.CV2021

-Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception

Dhaivat Bhatt, Kaustubh Mani, Dishank Bansal +3

While modern deep neural networks are performant perception modules, performance (accuracy) alone is insufficient, particularly for safety-critical robotic applications such as sel…

cs.RO2019

Deep Active Localization

Sai Krishna, Keehong Seo, Dhaivat Bhatt +3

Active localization is the problem of generating robot actions that allow it to maximally disambiguate its pose within a reference map. Traditional approaches to this use an inform…

math.OC2018

Chance Constraints Integrated MPC Navigation in Uncertainty amongst Dynamic Obstacles: An overlap of Gaussians approach

Dhaivat Bhatt, Akash Garg, Bharath Gopalakrishnan +1

In this paper, we formulate a novel trajectory optimization scheme that takes into consideration the state uncertainty of the robot and obstacle into its collision avoidance routin…