9 citations · 18 across the 9 of their papers we have counts for
9 papers
NeurOCS: Neural NOCS Supervision for Monocular 3D Object Localization
Zhixiang Min, Bingbing Zhuang, Samuel Schulter +3
Monocular 3D object localization in driving scenes is a crucial task, but challenging due to its ill-posed nature. Estimating 3D coordinates for each pixel on the object surface ho…
DDM-NET: End-to-end learning of keypoint feature Detection, Description and Matching for 3D localization
Xiangyu Xu, Li Guan, Enrique Dunn +2
In this paper, we propose an end-to-end framework that jointly learns keypoint detection, descriptor representation and cross-frame matching for the task of image-based 3D localiza…
HoloLens 2 Sensor Streaming
Juan C. Dibene, Enrique Dunn
We present a HoloLens 2 server application for streaming device data via TCP in real time. The server can stream data from the four grayscale cameras, depth sensor, IMU, front RGB…
LASER: LAtent SpacE Rendering for 2D Visual Localization
Zhixiang Min, Naji Khosravan, Zachary Bessinger +4
We present LASER, an image-based Monte Carlo Localization (MCL) framework for 2D floor maps. LASER introduces the concept of latent space rendering, where 2D pose hypotheses on the…
GTT-Net: Learned Generalized Trajectory Triangulation
Xiangyu Xu, Enrique Dunn
We present GTT-Net, a supervised learning framework for the reconstruction of sparse dynamic 3D geometry. We build on a graph-theoretic formulation of the generalized trajectory tr…
VOLDOR-SLAM: For the Times When Feature-Based or Direct Methods Are Not Good Enough
Zhixiang Min, Enrique Dunn
We present a dense-indirect SLAM system using external dense optical flows as input. We extend the recent probabilistic visual odometry model VOLDOR [Min et al. CVPR'20], by incorp…
VOLDOR: Visual Odometry from Log-logistic Dense Optical flow Residuals
Zhixiang Min, Yiding Yang, Enrique Dunn
We propose a dense indirect visual odometry method taking as input externally estimated optical flow fields instead of hand-crafted feature correspondences. We define our problem a…
Discrete Laplace Operator Estimation for Dynamic 3D Reconstruction
Xiangyu Xu, Enrique Dunn
We present a general paradigm for dynamic 3D reconstruction from multiple independent and uncontrolled image sources having arbitrary temporal sampling density and distribution. Ou…
Self-expressive Dictionary Learning for Dynamic 3D Reconstruction
Enliang Zheng, Dinghuang Ji, Enrique Dunn +1
We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a fram…