Author: Han-Pang Chiu
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Cross-View Visual Geo-Localization for Outdoor Augmented Reality
We address the problem of geo-pose estimation by cross-view matching of query ground images to a geo-referenced aerial satellite image database. Recently, neural network-based methods have shown state-of-the-art performance in cross-view matching.
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Autonomous Docking Using Learning-Based Scene Segmentation in Underground Mine Environments
This paper describes a vision-based autonomous docking solution that moves a coalmine shuttle car to the continuous miner in GPS-denied underground environments.
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Ranging-Aided Ground Robot Navigation Using UWB Nodes at Unknown Locations
This paper describes a new ranging-aided navigation approach that does not require the locations of ranging radios.
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Incremental Learning with Differentiable Architecture and Forgetting Search
In this paper, we show that leveraging NAS for incremental learning results in strong performance gains for classification tasks.
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Optimized Simultaneous Aided Target Detection and Imagery based Navigation in GPS-Denied Environments
We describe and demonstrate a comprehensive optimized vision-based real-time solution to provide SATIN capabilities for current and future UAS in GPS-denied environments.
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Cross-View and Cross-Modal Visual Geo-Localization for Augmented Reality and Robot/ Vehicle Navigation Applications
We will present methods and results for estimation of geo-location and/ or orientation for dismounts and platforms for wide area, outdoor augmented reality and other applications under GPS denied/ challenged conditions.
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Striking the Right Balance: Recall Loss for Semantic Segmentation
We propose a hard-class mining loss by reshaping the vanilla cross entropy loss such that it weights the loss for each class dynamically based on instantaneous recall performance.
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Graph Mapper: Efficient Visual Navigation by Scene Graph Generation
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.
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SASRA: Semantically-aware Spatio-temporal Reasoning Agent for Vision-and-Language Navigation in Continuous Environments
This paper presents a novel approach for the Vision-and-Language Navigation (VLN) task in continuous 3D environments.
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Head-Worn Markerless Augmented Reality Inside a Moving Vehicle
This paper describes a system that provides general head-worn outdoor AR capability for the user inside a moving vehicle.
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SIGNAV: Semantically-Informed GPS-Denied Navigation and Mapping in Visually-Degraded Environments
We present SIGNAV, a real-time semantic SLAM system to operate in perceptually-challenging situations.
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Long-Range Augmented Reality with Dynamic Occlusion Rendering
This paper addresses the problem of fast and accurate dynamic occlusion reasoning by real objects in the scene for large scale outdoor AR applications.