Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

625
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
625
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.4K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

MUFOLD-DB: a processed protein structure database for protein structure prediction and analysis.

BMC genomics·2015
Same author

The I-TASSER Suite: protein structure and function prediction.

Nature methods·2014
Same author

Genome-wide expression analysis of soybean NF-Y genes reveals potential function in development and drought response.

Molecular genetics and genomics : MGG·2014
Same author

Classification of lung cancer using ensemble-based feature selection and machine learning methods.

Molecular bioSystems·2014
Same author

Resveratrol possesses protective effects in a pristane-induced lupus mouse model.

PloS one·2014
Same author

Protein-losing enteropathy in systemic lupus erythematosus: 12 years experience from a Chinese academic center.

PloS one·2014
Same journal

A Unified and Fast-Sampling Diffusion Bridge Framework via Stochastic Optimal Control.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Robust 3D Semantic Occupancy Prediction With Calibration-Free Spatial Transformation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Image Restoration via Multi-domain Learning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Jun 21, 2025

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K

3D Reconstruction From a Single Sketch via View-Dependent Depth Sampling.

Chenjian Gao, Xilin Wang, Qian Yu

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |July 8, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces SketchSampler, a new method for 3D shape reconstruction from single sketches. It uses density maps and a two-stage sampling process to improve detail and accuracy in 3D object generation.

    More Related Videos

    Construction of a Realistic, Whole-Body, Three-Dimensional Equine Skeletal Model using Computed Tomography Data
    11:09

    Construction of a Realistic, Whole-Body, Three-Dimensional Equine Skeletal Model using Computed Tomography Data

    Published on: February 25, 2021

    3.1K
    3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
    10:14

    3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

    Published on: May 12, 2019

    7.3K

    Related Experiment Videos

    Last Updated: Jun 21, 2025

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    15.6K
    Construction of a Realistic, Whole-Body, Three-Dimensional Equine Skeletal Model using Computed Tomography Data
    11:09

    Construction of a Realistic, Whole-Body, Three-Dimensional Equine Skeletal Model using Computed Tomography Data

    Published on: February 25, 2021

    3.1K
    3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
    10:14

    3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

    Published on: May 12, 2019

    7.3K

    Area of Science:

    • Computer Vision
    • Computer Graphics
    • Artificial Intelligence

    Background:

    • Reconstructing 3D shapes from single sketches is difficult due to data sparsity and ambiguity.
    • Current methods often fail to preserve fine details during feature extraction for 3D object prediction.
    • Analyzing the 3D-to-2D projection reveals density maps as a viable proxy for aiding sketch-based reconstruction.

    Purpose of the Study:

    • To propose a novel sketch-based 3D reconstruction model, SketchSampler.
    • To improve the accuracy and detail preservation in 3D shape generation from 2D sketches.
    • To address the inherent ambiguity in sketch-based 3D reconstruction.

    Main Methods:

    • SketchSampler translates sketches into informative 2D representations using an image translation network.
    • A density map is generated from the 2D representation to guide the reconstruction process.
    • A two-stage probabilistic sampling reconstructs 3D point clouds by first sampling 2D points and then predicting depth (z-coordinate).
    • Hidden lines are incorporated into sketches to reduce ambiguity.
    • The reconstructed point cloud is converted into a 3D mesh.

    Main Results:

    • The proposed SketchSampler model significantly outperforms existing baseline methods in 3D reconstruction from sketches.
    • The density map approach effectively facilitates the reconstruction process.
    • The two-stage sampling method accurately recovers 3D point cloud coordinates.
    • Incorporating hidden lines aids in reducing reconstruction ambiguity.

    Conclusions:

    • SketchSampler offers a significant advancement in sketch-based 3D shape reconstruction.
    • The use of density maps and a novel sampling strategy enhances detail preservation and accuracy.
    • The method shows promise for wider applications through conversion to 3D meshes.