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Home » Archives for Rakesh Kumar
Rakesh Kumar

Rakesh Kumar

Vice President, Information and Computing Sciences Director, Center for Vision Technologies
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Publications

Computer vision publications May 18, 2022 Conference Paper

Graph Mapper: Efficient Visual Navigation by Scene Graph Generation

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

We propose a method to train an autonomous agent to learn to accumulate a 3D scene graph representation of its environment by simultaneously learning to navigate through said environment.

Computer vision publications May 18, 2022 Conference Paper

SASRA: Semantically-aware Spatio-temporal Reasoning Agent for Vision-and-Language Navigation in Continuous Environments

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

This paper presents a novel approach for the Vision-and-Language Navigation (VLN) task in continuous 3D environments.

2d-3d reasoning and augmented reality publications March 12, 2022 Conference Paper

Head-Worn Markerless Augmented Reality Inside a Moving Vehicle

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

This paper describes a system that provides general head-worn outdoor AR capability for the user inside a moving vehicle.

2d-3d reasoning and augmented reality publications October 8, 2021

Global Heading Estimation for Wide Area Augmented Reality Using Road Semantics for Geo-referencing

Supun Samarasekera, Rakesh Kumar

We present a method to estimate global camera head- ing by associating directional information from road segments in the camera view with annotated satellite imagery.

2d-3d reasoning and augmented reality publications August 27, 2021 Journal Article

Long-Range Augmented Reality with Dynamic Occlusion Rendering

Supun Samarasekera, Han-Pang Chiu, Rakesh Kumar

This paper addresses the problem of fast and accurate dynamic occlusion reasoning by real objects in the scene for large scale outdoor AR applications.

Computer vision publications May 30, 2021 Conference Paper

MaAST: Map Attention with Semantic Transformers for Efficient Visual Navigation

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

By using our novel attention schema and auxiliary rewards to better utilize scene semantics, we outperform multiple baselines trained with only raw inputs or implicit semantic information while operating with an 80% decrease in the agent’s experience.

2d-3d reasoning and augmented reality publications October 12, 2020

RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

We study an important, yet largely unexplored problem of large-scale cross-modal visual localization by matching ground RGB images to a geo-referenced aerial LIDAR 3D point cloud.

2d-3d reasoning and augmented reality publications September 9, 2019

Semantically-Aware Attentive Neural Embeddings for 2D Long-Term Visual Localization

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

We present an approach that combines appearance and semantic information for 2D image-based localization (2D-VL) across large perceptual changes and time lags.

Machine learning publications June 18, 2018

Evaluating Visual-Semantic Explanations using a Collaborative Image Guessing Game

Yi Yao, Rakesh Kumar

Abstract While there have been many proposals on making AI algorithms explainable, few have attempted to evaluate the impact of AI-generated explanations on human performance in conducting human-AI collaborative tasks. To bridge the gap, we propose a Twenty-Questions style collaborative image retrieval game, Explanation-assisted Guess Which (ExAG), as a method of evaluating the efficacy of […]

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