Conferences  >  Informatics  >  Multimedia, Computer Graphics and Visualization, Games

Ritsumeikan University, Japan

The advancements in computer vision, machine learning, and other related fields have led to an explosion of new techniques, tools, and applications for image and graphics processing. From deep learning-based image recognition to generative adversarial networks (GANs) for image synthesis, the possibilities are endless. This symposium provides a unique opportunity to exchange knowledge and ideas, as well as to network with leading experts in the field. We are excited to bring together researchers, engineers, and practitioners from around the world to share their latest findings, discuss emerging trends, and explore new directions.

Phone: [001-518-478-2659];     Email: aimee@iacsit.net

Track 1. Image Processing and Analysis - Image enhancement, restoration, and filtering - Image segmentation and object detection - Image compression, coding, and transmission - Medical image processing and analysis - Remote sensing and satellite image processing - Hyperspectral and multispectral image analysis Track 2. Computer Vision and Pattern Recognition - Object detection, tracking, and recognition - 3D vision and reconstruction - Motion analysis and action recognition - Scene understanding and semantic segmentation - Face, gesture, and pose recognition - Deep learning for computer vision tasks Track 3. Graphics and Visualization - Rendering techniques (real-time, photorealistic, non-photorealistic) - Geometric modeling and processing - Animation, simulation, and virtual reality - Augmented reality and mixed reality - Scientific and information visualization - GPU-based graphics and parallel computing

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Faithful data representation is key. While this is universally true for visual analysis, the field of biological data communication has its unique challenges and open questions. Researchers need the right context to interpret data accurately, especially when uncertainties arise from factors like sampling choices or analysis parameters. Simplifying data for wider audiences must still convey its complexity and uncertainty to support informed decisions. This Dagstuhl Seminar will bring together experts in data visualisation and design, researchers, public educators, and journalists to explore methods for embracing and communicating biodata complexity and uncertainty.

Scientific Computing and Data Science,    Human-Computer Interaction, User Experience, Virtual Reality

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

In this Dagstuhl Seminar, we aim to bring together researchers and industry practitioners who study and build digital games. The goal is to generate a better understanding of the harms in games and progress towards enriching playful experiences for broad groups of players.

games; toxicity; deceptive design; problematic gaming; accessibility;

Human-Computer Interaction, User Experience, Virtual Reality,    Social Networks and Social Aspects of Information Technology