Related papers: A three dimensional object point process for detec…
3D object detection has achieved remarkable progress by taking point clouds as the only input. However, point clouds often suffer from incomplete geometric structures and the lack of semantic information, which makes detectors hard to…
In order to enlarge publicly available optical cluster catalogs, in particular at high redshift, we have performed a systematic search for clusters of galaxies in the CFHTLS. We used the Le Phare photometric redshifts for the galaxies…
Conventional methods of 3D object generative modeling learn volumetric predictions using deep networks with 3D convolutional operations, which are direct analogies to classical 2D ones. However, these methods are computationally wasteful in…
3D object detection plays an important role in a large number of real-world applications. It requires us to estimate the localizations and the orientations of 3D objects in real scenes. In this paper, we present a new network architecture…
The detection and characterization of filamentary structures in the cosmic web allows cosmologists to constrain parameters that dictates the evolution of the Universe. While many filament estimators have been proposed, they generally lack…
We present a new 3D point-based detector model, named Shift-SSD, for precise 3D object detection in autonomous driving. Traditional point-based 3D object detectors often employ architectures that rely on a progressive downsampling of…
The three-point correlation function (3PCF) can now be measured in large galaxy redshift surveys, but in three dimensions its interpretation is complicated by the presence of redshift-space distortions. I investigate the projected 3PCF,…
In this paper we describe a set of models to predict the colours of galaxies over a wide range of redshifts. We present example output from the simulations, and discuss their application to the selection of galaxies at high redshifts,…
I review the statistical techniques needed to extract information about physical parameters of galaxies from their observed spectra. This is important given the sheer size of the next generation of large galaxy redshift surveys. Going to…
We developed a modification to the calculation of the two-point correlation function commonly used in the analysis of large scale structure in cosmology. An estimator of the two-point correlation function is constructed by contrasting the…
The problem of detecting dark matter filaments in the cosmic web is considered. Weak lensing is an ideal probe of dark matter, and therefore forms the basis of particularly promising detection methods. We consider and develop a number of…
Recent object detection systems rely on two critical steps: (1) a set of object proposals is predicted as efficiently as possible, and (2) this set of candidate proposals is then passed to an object classifier. Such approaches have been…
For more that seventy years, the measurements of fluxes of galaxies at different wavelengths and derived colours have been used to estimate their corresponding cosmological distances. From the fields of galaxy and AGN evolution to precision…
Thread-like structures are pervasive across scales, from polymeric proteins to root systems to galaxy filaments, and their characteristics can be readily investigated in the network formalism. Yet, network links usually represent only parts…
Line-Intensity Mapping (LIM) has emerged as a powerful technique for studying large-scale structure and the high-redshift universe, enabling three-dimensional maps of line emission across vast cosmological volumes. In this review, we…
Lidar based 3D object detection and classification tasks are essential for autonomous driving(AD). A lidar sensor can provide the 3D point cloud data reconstruction of the surrounding environment. However, real time detection in 3D point…
Clusters of galaxies are at the intersection of cosmic filaments and are still accreting galaxies and groups along these preferential directions, but, because of their relatively low contrast on the sky, they are difficult to detect (unless…
In this work, we address the problem of 3D object detection from point cloud data in real time. For autonomous vehicles to work, it is very important for the perception component to detect the real world objects with both high accuracy and…
In this paper we present a scale free method to determine the cosmological parameters (Omega_m, Omega_Lambda). The method is based on the requirement of isotropy of the distribution of orientations of cosmological filaments. The current…
Context. Filamentary structures appear to be ubiquitous in the interstellar medium. Being able to detect and characterize them is the first step toward understanding their origin, their evolution, and their role in the Galactic cycle of…