Search Results for author:
Found 17 papers, 5 papers with code
VRS-NeRF: Visual Relocalization with Sparse Neural Radiance Field
However, in spite of high efficiency, APRs and SCRs have limited accuracy especially in large-scale outdoor scenes; HMs are accurate but need to store a large number of 2D descriptors for matching, resulting in poor efficiency.
PRAM: Place Recognition Anywhere Model for Efficient Visual Localization
Humans localize themselves efficiently in known environments by first recognizing landmarks defined on certain objects and their spatial relationships, and then verifying the location by aligning detailed structures of recognized objects with those in the memory.
Individualized Dynamic Model for Multi-resolutional Data with Application to Mobile Health
In this paper, we propose an individualized dynamic latent factor model for irregular multi-resolution time series data to interpolate unsampled measurements of time series with low resolution.
IMP: Iterative Matching and Pose Estimation with Adaptive Pooling
Previous methods solve feature matching and pose estimation using a two-stage process by first finding matches and then estimating the pose.
Efficient Large-Scale Localization by Global Instance Recognition
Hierarchical frameworks consisting of both coarse and fine localization are often used as the standard pipeline for large-scale visual localization.
Statistical Inference for High-Dimensional Linear Regression with Blockwise Missing Data
Blockwise missing data occurs frequently when we integrate multisource or multimodality data where different sources or modalities contain complementary information.
Active Terahertz Imaging Dataset for Concealed Object Detection
Concealed object detection in Terahertz imaging is an urgent need for public security and counter-terrorism.
Current-induced torques in magnetic Weyl semimetal tunnel junctions
We study the current-induced torques in asymmetric magnetic tunnel junctions containing a conventional ferromagnet and a magnetic Weyl semimetal contact.
Mesoscale and Nanoscale Physics
Line Flow based SLAM
To address these problems, we leverage a line flow to encode the coherence of line segment observations of the same 3D line along the temporal dimension, which has been neglected in prior SLAM systems.
Learning Multi-View Camera Relocalization With Graph Neural Networks
We propose to construct a view graph to excavate the information of the whole given sequence for absolute camera pose estimation.
Ranked #3 on
Camera Localization
on Oxford RobotCar Full
Self-Supervised Deep Visual Odometry with Online Adaptation
In this paper, we propose an online meta-learning algorithm to enable VO networks to continuously adapt to new environments in a self-supervised manner.
Multicategory Angle-based Learning for Estimating Optimal Dynamic Treatment Regimes with Censored Data
An optimal dynamic treatment regime (DTR) consists of a sequence of decision rules in maximizing long-term benefits, which is applicable for chronic diseases such as HIV infection or cancer.
Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry
As single-view depth estimation is an ill-posed problem, and photometric loss is incapable of discriminating distortion artifacts of warped images, the estimated depth is vague and pose is inaccurate.
Local Supports Global: Deep Camera Relocalization with Sequence Enhancement
We propose to leverage the local information in image sequences to support global camera relocalization.
Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry
Most previous learning-based visual odometry (VO) methods take VO as a pure tracking problem.
Guided Feature Selection for Deep Visual Odometry
We present a novel end-to-end visual odometry architecture with guided feature selection based on deep convolutional recurrent neural networks.
