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GHNeRF: Learning Generalizable Human Features with Efficient Neural Radiance Fields
In this paper, we introduce a novel approach, termed GHNeRF, designed to address these limitations by learning 2D/3D joint locations of human subjects with NeRF representation.
HFNeRF: Learning Human Biomechanic Features with Neural Radiance Fields
In recent advancements in novel view synthesis, generalizable Neural Radiance Fields (NeRF) based methods applied to human subjects have shown remarkable results in generating novel views from few images.
Guaranteeing Service in Connected Microgrids: Storage Planning and Optimal Power Sharing Policy
To address this issue, battery energy sources (BESs) are being increasingly used as a promising solution to counter the uncertainty associated with RES power production.
DiVa-360: The Dynamic Visual Dataset for Immersive Neural Fields
Advances in neural fields are enabling high-fidelity capture of the shape and appearance of dynamic 3D scenes.
PNeRF: Probabilistic Neural Scene Representations for Uncertain 3D Visual Mapping
The aim of this paper is therefore to propose a novel method for training {\em probabilistic neural scene representations} with uncertain training data that could enable the inclusion of these representations in robotics applications.
Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact
Our weakly supervised models perform competitively with traditional supervised techniques and require less involvement from domain experts, demonstrating their use as efficient and practical alternatives to supervised learning in HC applications of ML.
Mip-NeRF RGB-D: Depth Assisted Fast Neural Radiance Fields
Neural scene representations, such as Neural Radiance Fields (NeRF), are based on training a multilayer perceptron (MLP) using a set of color images with known poses.
RGB-D Neural Radiance Fields: Local Sampling for Faster Training
Learning a 3D representation of a scene has been a challenging problem for decades in computer vision.
Urban Fire Station Location Planning using Predicted Demand and Service Quality Index
Finally, we develop an optimization problem to select best locations to install new fire stations.
Transactive Framework for Dynamic Energy Storage Allocation for Critical Load Management
Although the emerging transactive energy management techniques improve the grid reliability, the inherent uncertainty of RES poses a challenge in meeting the power demand of the critical infrastructure in the microgrid unless sufficient battery energy storage is maintained.
