202 citations · 296 across the 9 of their papers we have counts for
11 papers · 1 filter
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
Chao Qu, Wenxin Liu, Camillo J. Taylor
In this work we investigate the problem of uncertainty estimation for image-guided depth completion. We extend Deep Basis Fitting (DBF) for depth completion within a Bayesian evide…
PennSyn2Real: Training Object Recognition Models without Human Labeling
Ty Nguyen, Ian D. Miller, Avi Cohen +5
Scalable training data generation is a critical problem in deep learning. We propose PennSyn2Real - a photo-realistic synthetic dataset consisting of more than 100,000 4K images of…
Depth Completion via Deep Basis Fitting
Chao Qu, Ty Nguyen, Camillo J. Taylor
In this paper we consider the task of image-guided depth completion where our system must infer the depth at every pixel of an input image based on the image content and a sparse s…
PST900: RGB-Thermal Calibration, Dataset and Segmentation Network
Shreyas S. Shivakumar, Neil Rodrigues, Alex Zhou +3
In this work we propose long wave infrared (LWIR) imagery as a viable supporting modality for semantic segmentation using learning-based techniques. We first address the problem of…
MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based Tasks
Ty Nguyen, Shreyas S. Shivakumar, Ian D. Miller +9
Real-time semantic image segmentation on platforms subject to size, weight and power (SWaP) constraints is a key area of interest for air surveillance and inspection. In this work,…
DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance
Yilun Zhang, Ty Nguyen, Ian D. Miller +4
Depth estimation is an important capability for autonomous vehicles to understand and reconstruct 3D environments as well as avoid obstacles during the execution. Accurate depth se…