Author: Han-Pang Chiu
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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.
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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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Multi-Sensor Fusion for Motion Estimation in Visually-Degraded Environments
This paper analyzes the feasibility of utilizing multiple low-cost on-board sensors for ground robots or drones navigating in visually-degraded environments.
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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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Virtual Insertion: Robust Bundle Adjustment Over Long Video Sequences
Our goal is to circumvent one of the roadblocks of using existing bundle adjustment algorithms for achieving satisfactory large-area structure from motion over long video sequences, namely, the need for sufficient visual features tracked across consecutive frames.