Search Results for author:
Found 22 papers, 10 papers with code
Behind the Veil: Enhanced Indoor 3D Scene Reconstruction with Occluded Surfaces Completion
The 3D Inpainter with abstract representation at coarse levels is trained offline using various scenes to complete occluded surfaces.
TCLC-GS: Tightly Coupled LiDAR-Camera Gaussian Splatting for Surrounding Autonomous Driving Scenes
Most 3D Gaussian Splatting (3D-GS) based methods for urban scenes initialize 3D Gaussians directly with 3D LiDAR points, which not only underutilizes LiDAR data capabilities but also overlooks the potential advantages of fusing LiDAR with camera data.
UPNeRF: A Unified Framework for Monocular 3D Object Reconstruction and Pose Estimation
Monocular 3D reconstruction for categorical objects heavily relies on accurately perceiving each object's pose.
3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection
A major challenge in monocular 3D object detection is the limited diversity and quantity of objects in real datasets.
Tracking performance of PID for nonlinear stochastic systems
In this paper, we will consider a class of continuous-time stochastic control systems with both unknown nonlinear structure and unknown disturbances, and investigate the capability of the classical proportional-integral-derivative(PID) controller in tracking time-varying reference signals.
Understanding the Capability of PD Control for Uncertain Stochastic Systems
In this article, we focus on the global stabilizability problem for a class of second order uncertain stochastic control systems, where both the drift term and the diffusion term are nonlinear functions of the state variables and the control variables.
EventPoint: Self-Supervised Interest Point Detection and Description for Event-based Camera
We propose a new time-surface-like event stream representation method called Tencode.
NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation
Benefiting from the NDT representation and NDT-Transformer network, the learned global descriptors are enriched with both geometrical and contextual information.
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the BAO and growth rate of structure of the luminous red galaxy sample from the anisotropic correlation function between redshifts 0.6 and 1
We present the cosmological analysis of the configuration-space anisotropic clustering in the completed Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 galaxy sample.
Cosmology and Nongalactic Astrophysics
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the Halo Occupation Distribution model of Emission Line Galaxies
We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: a multi-tracer analysis in Fourier space for measuring the cosmic structure growth and expansion rate
We perform a joint BAO and RSD analysis using the eBOSS DR16 LRG and ELG samples in the redshift range of $z\in[0. 6, 1. 1]$, and detect a RSD signal from the cross power spectrum at a $\sim4\sigma$ confidence level, i. e., $f\sigma_8=0. 317\pm0. 080$ at $z_{\rm eff}=0. 77$.
Cosmology and Nongalactic Astrophysics
The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR16 luminous red galaxy and emission line galaxy samples: cosmic distance and structure growth measurements using multiple tracers in configuration space
We perform a multi-tracer analysis using the complete Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 luminous red galaxy (LRG) and the DR16 emission line galaxy (ELG) samples in the configuration space, and successfully detect a cross correlation between the two samples, and find the growth rate to be $f\sigma_8=0. 342 \pm 0. 085$ ($\sim25$ per cent accuracy) from the cross sample alone.
Cosmology and Nongalactic Astrophysics
CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network
Given two relevant domains (e. g., Book and Movie), users may have interactions with items in one domain but not in the other domain.
Cross-Domain Recommendation via Preference Propagation GraphNet
We find there are mainly three problems in their formulations: 1) their knowledge transfer is unaware of the cross-domain graph structure.
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
In order to integrate uncertainty estimates into deep time-series modelling, Kalman Filters (KFs) (Kalman et al., 1960) have been integrated with deep learning models, however, such approaches typically rely on approximate inference techniques such as variational inference which makes learning more complex and often less scalable due to approximation errors.
Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data
Most existing semantic mapping approaches focus on improving semantic understanding of single frames, rather than 3D refinement of semantic maps (i. e. fusing semantic observations).
Learning monocular visual odometry with dense 3D mapping from dense 3D flow
Dense 2D flow and a depth image are generated from monocular images by sub-networks, which are then used by a 3D flow associated layer in the L-VO network to generate dense 3D flow.
SPP-Net: Deep Absolute Pose Regression with Synthetic Views
In this work we design a deep neural network architecture based on sparse feature descriptors to estimate the absolute pose of an image.
Dense RGB-D semantic mapping with Pixel-Voxel neural network
For intelligent robotics applications, extending 3D mapping to 3D semantic mapping enables robots to, not only localize themselves with respect to the scene's geometrical features but also simultaneously understand the higher level meaning of the scene contexts.
The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: a tomographic analysis of structure growth and expansion rate from anisotropic galaxy clustering
In order to extract the redshift information of anisotropic galaxy clustering, we analyse this data set in nine overlapping redshift slices in configuration space and perform the joint constraints on the parameters $(D_V, F_{\mathrm{AP}}, f\sigma_8)$ using the correlation function multipoles.
Cosmology and Nongalactic Astrophysics
Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data
We also propose a novel way to pretrain a DCNN for the depth modality, by training on virtual depth images projected from CAD models.
A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition
We present the results of experiments, in which we trained our system to perform real-time 3D semantic reconstruction for 23 different materials in a real-world application.
