23 papers · ranked by Valyu relevance
Emil Dumic, Anamaria Bjelopera, Andreas Nüchter, Steve Vanlanduit
In this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for obtained geometry and texture maps. Texture maps have been compressed after creating Voronoi diagrams. Used video…
Qiang Wang, Liuyang Jiang, Xuebin Sun, Jingbo Zhao + 4 more
'Shizhong Yang' 'Baochang Zhang' 'Ying Huang'] In this article, we present an efficient coding scheme for LiDAR point cloud maps. As a point cloud map consists of numerous single scans spliced together, by recording the time stamp and quaternion matrix of each scan during map building, we cast the point cloud map…
Qingyang Zhou, Shan Liu, C.‐C. Jay Kuo
A low-complexity point cloud compression method called the Green Point Cloud Geometry Codec (GPCGC), is proposed to encode the 3D spatial coordinates of static point clouds efficiently. GPCGC consists of two modules. In the first module, point coordinates of input point clouds are hierarchically organized into an…
Jiawen Yu, Jin Wang, Longhua Sun, Mu-En Wu + 3 more
'Jose Santamaria' 'Francisco Roca'] Point cloud data are extensively used in various applications, such as autonomous driving and augmented reality since it can provide both detailed and realistic depictions of 3D scenes or objects. Meanwhile, 3D point clouds generally occupy a large amount of storage space that is a…
Hoda Roodaki, Mahdi Nazm Bojnordi
—The ever-increasing demand for 3D modeling in the emerging immersive applications has made point clouds an essential class of data for 3D image and video processing. Treebased structures are commonly used for representing point clouds where pointers are used to realize the connection between nodes. Tree-based…
Luís Garrote, João Perdiz, Luís A. da Silva Cruz, Urbano J. Nunes + 2 more
'Manuel F. Silva' 'Marcelo Petry'] Increasing demand for more reliable and safe autonomous driving means that data involved in the various aspects of perception, such as object detection, will become more granular as the number and resolution of sensors progress. Using these data for on-the-fly object detection causes…
Nguyen Quang Hieu, Minh Anh Nguyen, Dinh Thai Hoang, Diep N. Nguyen + 1 more
'Eryk Dutkiewicz'] Abstract— This paper introduces a novel lossless compression method for compressing geometric attributes of point cloud data with bits-back coding. Our method specializes in using a deep learning-based probabilistic model to estimate the Shannon's entropy of the point cloud information, i.e.…
Jin-Kyum Kim, Ye-Won Jang, Sol Lee, Eui-Seok Hwang + 3 more
'Stefano Berretti' 'Ruben Pauwels'] This paper proposes an algorithm for transmitting and reconstructing the estimated point cloud by temporally estimating a dynamic point cloud sequence. When a non-rigid 3D point cloud sequence (PCS) is input, the sequence is divided into groups of point cloud frames (PCFs), and a key…
Yueyu Hu, Ran Gong, Yao Wang
Direct Rendering Authors: ['Yueyu Hu' 'Ran Gong' 'Yao Wang'] > Abstract. Point cloud is a promising 3D representation for volumetric streaming in emerging AR/VR applications. Despite recent advances in point cloud compression, decoding and rendering high-quality images from lossy compressed point clouds is still…
Bert Van hauwermeiren, Leon Denis, Adrian Munteanu, Yuemin Zhu
Point cloud compression is essential for the efficient storage and transmission of 3D data in various applications, such as virtual reality, autonomous driving, and 3D modelling. Most existing compression methods employ voxelisation, all of which uniformly partition 3D space into voxels for more efficient compression.…
Joao Prazeres, Rafael Rodrigues, Manuela Pereira, Antonio M. G. Pinheiro
'Antonio M. G. Pinheiro'] Abstract—Full-reference point cloud objective metrics are currently providing very accurate representations of perceptual quality. These metrics are usually composed of a set of features that are somehow combined, resulting in a final quality value. In this study, the different features of the…
Dingquan Li, Kede Ma, Jing Wang, Ge Li
Compression Authors: ['Dingquan Li' 'Kede Ma' 'Jing Wang' 'Ge Li'] Abstract—The Geometry-based Point Cloud Compression (G-PCC) has been developed by the Moving Picture Experts Group to compress point clouds. In its lossy mode, the reconstructed point cloud by G-PCC often suffers from noticeable distortions due to the…
Faranak Tohidi, Manoranjan Paul, Anwaar Ulhaq, Subrata Chakraborty + 1 more
A point cloud is a representation of objects or scenes utilising unordered points comprising 3D positions and attributes. The ability of point clouds to mimic natural forms has gained significant attention from diverse applied fields, such as virtual reality and augmented reality. However, the point cloud, especially…
Viet Thanh Duy Nguyen, Truong Son Hy
In this paper, we introduce a framework of symmetry-preserving multimodal pretraining to learn a unified representation on proteins in an unsupervised manner that can take into account primary and tertiary structures. For each structure, we propose the corresponding pretraining method on sequence, graph, and 3D point…
Ritvik Vasan, Alexandra Ferrante, Antoine Borensztejn, Christopher L. Frick + 7 more
A key challenge in understanding subcellular organization is quantifying interpretable measurements of intracellular structures with complex multi-piece morphologies in an objective, robust and generalizable manner. Here we introduce a morphology-appropriate representation learning framework that uses 3D rotation…
Authors not listed
The screening of chemical libraries is an essential starting point in the drug discovery process. While some researchers desire a more thorough screening of drug targets against a narrower scope of molecules, it is not uncommon for diverse screening sets to be favored during early stages of drug discovery. However, a…
Atsushi Hayashi, Nobuo Kochi, Kunihiro Kodama, Sachiko Isobe + 1 more
This research proposes a novel technique for acquiring a large amount of high-density, high-precision 3D point cloud data for plants. We propose two methods, multi-masked matching (MMM) and the closed-loop coarse-to-fine method (CLCFM). The proposed approach addresses challenges in reconstructing plant 3D point clouds…
David Meijer, Marnix H. Medema, Justin J. J. van der Hooft
Effective visualization of small molecules is paramount in conveying concepts and results in cheminformatics. Scalable vector graphics (SVG) are preferred for creating such visualizations, as SVGs can be easily altered in post-production and exported to other formats. A wide spectrum of software applications already…
James P. Bohnslav, Mohammed Abdal Monium Osman, Akshay Jaggi, Sofia Soares + 3 more
Characterizing animal behavior requires methods to distill 3D movements from video data. Though keypoint tracking has emerged as a widely used solution to this problem, it only provides a limited view of pose, reducing the body of an animal to a sparse set of experimenter-defined points. To more completely capture 3D…
Authors not listed
Olfaction arises from the interaction of odorants with olfactory receptors, a process shaped by molecular geometry, electron distribution, and conformational preference. We present ConfDENSE, a Set2Set enhanced PointNet model that learns directly from Hirshfeld promolecule electron-density point clouds, preserving full…
Shuntaro C. Aoki, Reo Tsukasa, Shiyun Yang, Misato Tanaka + 4 more
The human brain assembles three-dimensional (3D) percepts from qualitatively different depth cues, yet the perceived 3D structure that the brain builds—a representation shared across cues—has remained difficult to measure directly. Here, we show that this cue-invariant 3D structure can be externalized as explicit 3D…
Yiming Zeng, Junhui Hou, Qijian Zhang, Siyu Ren + 1 more
—Dynamic 3D point cloud sequences serve as one of the most common and practical representation modalities of dynamic real-world environments. However, their unstructured nature in both spatial and temporal domains poses significant challenges to effective and efficient processing. Existing deep point cloud sequence…
Jie Lin, Mingyuan Xu, Hongming Chen
Shape-based virtual screening is a widely utilized method in ligand-based de novo drug design, aiming to identify molecules in chemical libraries that share similar 3D shapes but simultaneously possess novel 2D chemical structures compared to the reference compound. As an emerging technology, generative model is an…