9 citations · 16 across the 6 of their papers we have counts for
7 papers · 1 filter
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…
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…