1 code implementation • 10 Apr 2024 • Sibeak Lee, Kyeongsu Kang, Hyeonwoo Yu
We present the Bayesian Neural Radiance Field (NeRF), which explicitly quantifies uncertainty in geometric volume structures without the need for additional networks, making it adept for challenging observations and uncontrolled images.
1 code implementation • 19 Mar 2024 • Seongbo Ha, Jiung Yeon, Hyeonwoo Yu
Simultaneous Localization and Mapping (SLAM) with dense representation plays a key role in robotics, Virtual Reality (VR), and Augmented Reality (AR) applications.
no code implementations • 14 Apr 2021 • Hyeonwoo Yu, Jean Oh
Therefore, we propose a strategy to exploit multipleobservations of the object in the image sequence in orderto surpass the self-performance: first, the landmarks for theglobal object map are estimated through network predic-tion and data association, and the corrected annotation fora single frame is obtained.
no code implementations • 12 Apr 2021 • Fei Lu, Hyeonwoo Yu, Jean Oh
The advent of deep learning has brought an impressive advance to monocular depth estimation, e. g., supervised monocular depth estimation has been thoroughly investigated.
no code implementations • 25 Jan 2021 • Hyeonwoo Yu, Jean Oh
Given a 2D Bounding Box (BBox) and object parameters, a 3D distance to the object can be calculated directly using 3D reprojection; however, such methods are prone to significant errors because an error from the 2D detection can be amplified in 3D.
no code implementations • 25 Jan 2021 • Hyeonwoo Yu, Jean Oh
In this context, we propose a method for imputation of latent variables whose elements are partially lost.
1 code implementation • NeurIPS 2019 • Hyeonwoo Yu, Beomhee Lee
To overcome the absence of training data for unseen classes, conventional zero-shot learning approaches mainly train their model on seen datapoints and leverage the semantic descriptions for both seen and unseen classes.
1 code implementation • 23 Jul 2019 • Hyeonwoo Yu
We present NOLBO, a variational observation model estimation for 3D multi-object from 2D single shot.