Author: Rakesh Kumar
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MaAST: Map Attention with Semantic Transformers for Efficient Visual Navigation
Through this work, we design a novel approach that focuses on performing better or comparable to the existing learning-based solutions but under a clear time/computational budget.
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RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization
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.
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Semantically-Aware Attentive Neural Embeddings for 2D Long-Term Visual Localization
We present an approach that combines appearance and semantic information for 2D image-based localization (2D-VL) across large perceptual changes and time lags.
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Evaluating Visual-Semantic Explanations using a Collaborative Image Guessing Game
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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Augmented Reality Driving Using Semantic Geo-Registration
We propose a new approach that utilizes semantic information to register 2D monocular video frames to the world using 3D georeferenced data, for augmented reality driving applications.
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Utilizing Semantic Visual Landmarks for Precise Vehicle Navigation
This paper presents a new approach for integrating semantic information for vision-based vehicle navigation.
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Sub-Meter Vehicle Navigation Using Efficient Pre-Mapped Visual Landmarks
This paper presents a vehicle navigation system that is capable of achieving sub-meter GPS-denied navigation accuracy in large-scale urban environments, using pre-mapped visual landmarks.
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AR-Weapon: Live Augmented Reality Based First-Person Shooting System
This paper introduces a user-worn Augmented Reality (AR) based first-person weapon shooting system (AR-Weapon), suitable for both training and gaming.
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AR-Mentor: Augmented Reality Based Mentoring System
The system combines a wearable Optical-See-Through (OST) display device with high precision 6-Degree-Of-Freedom (DOF) pose tracking and a virtual personal assistant (VPA) with natural language, verbal conversational interaction, providing guidance to the user in the form of visual, audio and locational cues.
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Augmented Reality Binoculars on the Move
We present our latest improvements and additions to our pose estimation pipeline and demonstrate stable registration of objects on the real world scenery while the binoculars are undergoing significant amount of parallax-inducing translation.
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Precise Vision-Aided Aerial Navigation
This paper proposes a novel vision-aided navigation approach that continuously estimates precise 3D absolute pose for aerial vehicles, using only inertial measurements and monocular camera observations.
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Constrained Optimal Selection for Multi-Sensor Robot Navigation Using Plug-and-Play Factor Graphs
This paper proposes a real-time navigation approach that is able to integrate many sensor types while fulfilling performance needs and system constraints.