Conference Information
VISAPP 2023: International Conference on Computer Vision Theory and Applications
https://visapp.scitevents.org/
Submission Date:
2022-10-10
Notification Date:
2022-12-06
Conference Date:
2023-02-19
Location:
Lisbon, Portugal
Years:
18
CORE: c   QUALIS: b3   Viewed: 22134   Tracked: 16   Attend: 7

Call For Papers
SCOPE

The International Conference on Computer Vision Theory and Applications aims at becoming a major point of contact between researchers, engineers and practitioners on the area of computer vision application systems. Five simultaneous tracks will be held, covering all different aspects related to computer vision: Image Formation and Preprocessing; Image and Video Analysis and Understanding; Motion, Tracking and Stereo Vision; and Applications and Services. We welcome papers describing original work in any of the areas listed below. Papers describing advanced prototypes, systems, tools and techniques as well as general survey papers indicating future directions are also encouraged. Paper acceptance will be based on quality, relevance to the conference themes and originality. The conference program will include both oral and poster presentations. Special sessions, dedicated to case-studies and commercial presentations, as well as technical tutorials, dedicated to technical/scientific topics, are also envisaged.

CONFERENCE AREAS

The last decade has seen a revolution in the theory and application of Artificial Intelligence and Machine Learning in Computer Vision. In this conference edition, we look at advanced in Computer Vision based on Machine Learning methods. Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas:

1. IMAGE AND VIDEO PROCESSING AND ANALYSIS
2. IMAGE AND VIDEO UNDERSTANDING
3. MOTION, TRACKING AND STEREO VISION
4. MOBILE AND EGOCENTRIC VISION FOR HUMANS AND ROBOTS
5. APPLICATIONS AND SERVICES

AREA 1: IMAGE AND VIDEO PROCESSING AND ANALYSIS

    Image Formation, Acquisition Devices and Sensors
    Device Calibration, Characterization and Modeling
    Image Enhancement and Restoration
    Image and Video Coding and Compression
    Multimodal and Multi-Sensor Models of Image Formation
    Image Registration
    Segmentation and Grouping
    Early and Biologically-Inspired Vision
    Color and Texture Analyses
    Shape Representation and Matching
    Features Extraction
    Visual Attention and Image Saliency

AREA 2: IMAGE AND VIDEO UNDERSTANDING

    Deep Learning for Visual Understanding
    Machine Learning Technologies for Vision
    Face and Expression Recognition
    Content-Based Indexing, Search, and Retrieval
    Object and Face Recognition
    Object Detection and Localization
    Categorization and Scene Understanding
    Event and Human Activity Recognition
    Few Shot Learning
    Transfer Learning
    Domain Adaptation
    Multi-task learning
    Self-taught Learning

AREA 3: MOTION, TRACKING AND STEREO VISION

    Image-Based Modeling and 3D Reconstruction
    Stereo Vision and Structure from Motion
    Simultaneous Localization and Mapping
    Optical Flow and Motion Analyses
    Tracking and Visual Navigation
    Video Surveillance and Event Detection

AREA 4: MOBILE AND EGOCENTRIC VISION FOR HUMANS AND ROBOTS

    Deep Learning for Tracking
    3D Deep Learning
    Mobile and Egocentric Object Detection and Recognition
    Mobile and Egocentric Localization
    Egocentric Vision for Interaction Understanding
    Mobile Vision
    Vision for Robotics

AREA 5: APPLICATIONS AND SERVICES

    Entertainment Imaging Applications
    Multimedia Forensics
    Assistive Computer Vision
    Mobile Imaging
    Imaging and Vision for Cultural Heritage
    Camera Networks and Vision
    Document Imaging in Business
    Medical Image Applications
    Human and Computer Interaction
Last updated by Dou Sun in 2022-09-11
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