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20122022
most citedTLIO: Tight Learned Inertial Odometry

225 citations · 628 across the 30 of their papers we have counts for

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10 papers · 1 filter

cs.CV2020

Place Recognition in Forests with Urquhart Tessellations

Guilherme V. Nardari, Avraham Cohen, Steven W. Chen +4

In this letter, we present a novel descriptor based on Urquhart tessellations derived from the position of trees in a forest. We propose a framework that uses these descriptors to…

cs.CV2020

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…

cs.CV2019

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…

cs.CV2019

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,…

cs.CV2019

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…

cs.CV2018

Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion

Alex Zihao Zhu, Wenxin Liu, Ziyun Wang +2

In this work, we propose a method that combines unsupervised deep learning predictions for optical flow and monocular disparity with a model based optimization procedure for instan…