Computer vision publications
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Global Heading Estimation for Wide Area Augmented Reality Using Road Semantics for Geo-referencing
We present a method to estimate global camera heading by associating directional information from road segments in the camera view with annotated satellite imagery.
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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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“How to best say it?” : Translating Directives in Machine Language into Natural Language in the Blocks World
We propose a method to generate optimal natural language for block placement directives generated by a machine's planner during human-agent interactions in the blocks world.
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Comprehension Based Question Answering Using Bloom’s Taxonomy
Our experiments focus on zero-shot question answering, using the taxonomy to provide proximal context that helps the model answer questions by being relevant to those questions.
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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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Towards Explainable Student Group Collaboration Assessment Models Using Temporal Representations of Individual Student Role and Behavioral Cues
In this paper we propose using simple temporal-CNN deep-learning models to assess student group collaboration that take in temporal representations of individual student roles as input.
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Hyper-Dimensional Analytics of Video Action at the Tactical Edge
We review HyDRATE, a low-SWaP reconfigurable neural network architecture developed under the DARPA AIE HyDDENN (Hyper-Dimensional Data Enabled Neural Network) program.
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Modular Adaptation for Cross-Domain Few-Shot Learning
While literature has demonstrated great successes via representation learning, in this work, we show that improvement of downstream tasks can also be achieved by appropriate designs of the adaptation process.
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Confidence Calibration for Domain Generalization under Covariate Shift
We present novel calibration solutions via domain generalization. Our core idea is to leverage multiple calibration domains to reduce the effective distribution disparity between the target and calibration domains for…
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Hybrid Consistency Training with Prototype Adaptation for Few-Shot Learning
We introduce Hybrid Consistency Training to jointly leverage interpolation consistency, including interpolating hidden features, that imposes linear behavior locally and data augmentation consistency that learns robust embeddings against sample variations.
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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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Lifelong learning using Eigentasks: Task separation, skill acquisition, and selective transfer
We introduce the eigentask framework for lifelong learning. An eigentask is a pairing of a skill that solves a set of related tasks, paired with a generative model that can…