6 papers
Single Image Super-Resolution via a Dual Interactive Implicit Neural Network
Quan H. Nguyen, William J. Beksi
In this paper, we introduce a novel implicit neural network for the task of single image super-resolution at arbitrary scale factors. To do this, we represent an image as a decodin…
Variable Rate Compression for Raw 3D Point Clouds
Md Ahmed Al Muzaddid, William J. Beksi
In this paper, we propose a novel variable rate deep compression architecture that operates on raw 3D point cloud data. The majority of learning-based point cloud compression metho…
An Uncertainty Estimation Framework for Probabilistic Object Detection
Zongyao Lyu, Nolan B. Gutierrez, William J. Beksi
In this paper, we introduce a new technique that combines two popular methods to estimate uncertainty in object detection. Quantifying uncertainty is critical in real-world robotic…
Learning the Next Best View for 3D Point Clouds via Topological Features
Christopher Collander, William J. Beksi, Manfred Huber
In this paper, we introduce a reinforcement learning approach utilizing a novel topology-based information gain metric for directing the next best view of a noisy 3D sensor. The me…
A Progressive Conditional Generative Adversarial Network for Generating Dense and Colored 3D Point Clouds
Mohammad Samiul Arshad, William J. Beksi
In this paper, we introduce a novel conditional generative adversarial network that creates dense 3D point clouds, with color, for assorted classes of objects in an unsupervised ma…
Camera-Based Adaptive Trajectory Guidance via Neural Networks
Aditya Rajguru, Christopher Collander, William J. Beksi
In this paper, we introduce a novel method to capture visual trajectories for navigating an indoor robot in dynamic settings using streaming image data. First, an image processing…