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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Fuzzy objects composed of hair, fur, or feather are impossible to scan even with the latest active or passive 3D scanners. We present a novel and practical neural rendering (NR) technique called neural opacity point cloud (NOPC) to allow high quality rendering of such fuzzy objects at any viewpoint.
Cen Wang +5 more
openaire +3 more sources
Fuzzy objects composed of hair, fur, or feather are impossible to scan even with the latest active or passive 3D scanners. We present a novel and practical neural rendering (NR) technique called neural opacity point cloud (NOPC) to allow high quality rendering of such fuzzy objects at any viewpoint.
Cen Wang +5 more
openaire +3 more sources
Point Cloud Mamba: Point Cloud Learning via State Space Model
AAAI Conference on Artificial IntelligenceRecently, state space models have exhibited strong global modeling capabilities and linear computational complexity in contrast to transformers. This research focuses on applying such architecture to more efficiently and effectively model point cloud ...
Tao Zhang +4 more
semanticscholar +1 more source
EGST: Enhanced Geometric Structure Transformer for Point Cloud Registration
IEEE Transactions on Visualization and Computer Graphics, 2023We explore the effect of geometric structure descriptors on extracting reliable correspondences and obtaining accurate registration for point cloud registration.
Yongzhe Yuan +5 more
semanticscholar +1 more source
, 2020
Pomegranate peel is a potential source of polyphenols, antioxidants, pectin, organic acids. Cloud point extraction (CPE) process parameters were optimized for efficient separation of polyphenols.
Pooja D. Motikar, P. More, S. Arya
semanticscholar +1 more source
Pomegranate peel is a potential source of polyphenols, antioxidants, pectin, organic acids. Cloud point extraction (CPE) process parameters were optimized for efficient separation of polyphenols.
Pooja D. Motikar, P. More, S. Arya
semanticscholar +1 more source
Proceedings of the 26th International Conference on Scientific and Statistical Database Management, 2014
We introduce the concept of the point cloud database, a new kind of database system aimed primarily towards scientific applications. Many scientific observations, experiments, feature extraction algorithms and large-scale simulations produce enormous amounts of data that are better represented as sparse (but often highly-clustered) points in a k ...
László Dobos +4 more
openaire +2 more sources
We introduce the concept of the point cloud database, a new kind of database system aimed primarily towards scientific applications. Many scientific observations, experiments, feature extraction algorithms and large-scale simulations produce enormous amounts of data that are better represented as sparse (but often highly-clustered) points in a k ...
László Dobos +4 more
openaire +2 more sources
Prediction of Cloud Points of Biodiesel
Energy & Fuels, 2007The predictive UNIQUAC model, previously applied with success to the description of wax formation in fossil fuels, is extended here to the modeling of the precipitation of saturated and unsaturated fatty acid methyl/ethyl esters. Correlations for the thermophysical properties of the fatty acid esters are proposed, and the model is evaluated against ...
Lopes, J. +7 more
openaire +3 more sources
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
European Conference on Computer Vision, 2020Arguably one of the top success stories of deep learning is transfer learning. The finding that pre-training a network on a rich source set (eg., ImageNet) can help boost performance once fine-tuned on a usually much smaller target set, has been ...
Saining Xie +5 more
semanticscholar +1 more source
Structure Aware Single-Stage 3D Object Detection From Point Cloud
Computer Vision and Pattern Recognition, 20203D object detection from point cloud data plays an essential role in autonomous driving. Current single-stage detectors are efficient by progressively downscaling the 3D point clouds in a fully convolutional manner.
Chenhang He +4 more
semanticscholar +1 more source
2017
Phase separation of a surfactant-loaded solution happens beyond a certain critical thermodynamic state (known as the cloud point), separating the hydrophobic-rich phase in a nonpolar microenvironment from the aqueous supernatant. The dye molecules are bounded to the surfactant and subsequently separated by changing the environmental factor (temperature
Sirshendu De +2 more
openaire +2 more sources
Phase separation of a surfactant-loaded solution happens beyond a certain critical thermodynamic state (known as the cloud point), separating the hydrophobic-rich phase in a nonpolar microenvironment from the aqueous supernatant. The dye molecules are bounded to the surfactant and subsequently separated by changing the environmental factor (temperature
Sirshendu De +2 more
openaire +2 more sources
Compression of Plenoptic Point Clouds
IEEE Transactions on Image Processing, 2019Point clouds have been recently used in applications involving real-time capture and rendering of 3D objects. In a point cloud, for practical reasons, each point or voxel is usually associated with one single color along with other attributes. The region-adaptive hierarchical transform (RAHT) coder has been proposed for single-color point clouds.
Gustavo Sandri +2 more
openaire +3 more sources