中国计算机学会（CCF）推荐学术会议-C（计算机图形学与多媒体）：PacificVis 2026

PacificVis 2026

IEEE Pacific Visualization Conference (PacificVis) was born in Kyoto in 2008 as an international event sponsored by IEEE Computer Society with the aim of promoting visualization research and technologies, especially in the Asian-Pacific region.

重要信息

CCF推荐：C（计算机图形学与多媒体）

录用率：30.3%（2024年）

时间地点：2026年4月20日-悉尼·澳大利亚

截止时间：2025年11月1日

大会官网：https://pacificvis2026.github.io/

Common call for papers

IEEE PacificVis 2026 solicits novel research contributions and innovative applications in all areas of visualization. PacificVis is a unified visualization conference covering topics including visualization techniques and systems, interactions, analytics and decision support, theoretical contributions to visualization, empirical studies, and visualization applications in domains such as (but not limited to) biological sciences, education, machine learning, physical sciences, security, and social science.

Paper Topics

1. Visualization Techniques

1.1. Visualization Techniques for a Broad Range of Data Types:

High-dimensional Data, Dimensionality Reduction, and Data Compression

Graphs and Networks

Text and Documents

Multi-field, Multimodal, Multi-resolution, and Multivariate Data

Causality and Uncertainty Data

Time Series, Time-varying, Streaming, and Flow Data

Scalar, Vector, and Tensor Fields

Regular and Unstructured Grids

Point-based Data

Large-scale Data

1.2. Visual Encoding, Feature Extraction, and Rendering Techniques:

Volume Modeling and Rendering

Visual Design and Aesthetics

Illustrative Visualization

Extraction of Surfaces

Topology-based and Geometry-based Techniques

Icon- and Glyph-based Techniques

Integrating Spatial and Non-spatial Data Visualization

1.3. Interaction Techniques for Supporting Data Analysis and Exploration:

Animation

Coordinated Multiple Views and Brushing & Linking

Data Labeling, Editing, and Annotation

Collaborative, Co-located, and Distributed Visualization

Manipulation and Deformation

Visual Data Mining and Visual Knowledge Discovery

Data Storytelling

Natural Language, Gesture, and Multimodal Interaction

1.4. Hardware, Display, and Interaction Technologies for Visualization:

Large and High-resolution Displays

Stereo Displays

Mobile and Ubiquitous Environments

Situated and Immersive Analytics

Data physicalization

Multimodal Input (Touch, Haptics, Voice, etc.)

Hardware Architectures for Visualization

1.5. VIS x AI:

Visualization for AI Explainability, Security, and Privacy

Visualization for AI Data Collection, Training, and Deployment

AI for Visualization Generation and Data Analysis

Machine Learning Assisted Visualization

LLMs and Generative Models

2. Systems

System Taxonomies and Design Patterns

Methodologies, Discussions, and Frameworks

Visual Analysis Systems, and Visualization Toolkits

Visual Data Warehousing, Database Visualization, and Visual Data Mining Systems

Collaborative and Distributed Visualization Systems

3. Applications & Design Studies

Statistical Graphics and Mathematics

Financial, Security, and Business Visualization

Physical Sciences and Engineering

Earth, Space, and Environmental Sciences

Geographic, Geospatial, and Terrain Visualization

Molecular, Biomedical, Bioinformatics, and Medical Visualization

Software Visualization

Machine Learning Visualization

Social and Information Sciences

Education and Everyday Visualization

Multimedia (Image/Video/Music) Visualization

4. Evaluation & Empirical Research

Qualitative evaluation

Quantitative evaluation

Laboratory studies

Field studies

Usability studies

Longitudinal studies

Metrics and Benchmarks

Use of Eye Tracking and Other Biometric Measures

5. Visualization Theory

Cognition and Perception

Frameworks and Models for Visualization or Interaction

New methodologies for visualization research and design

Visualization guidelines and heuristics

Taxonomies and ontologies

Mathematical abstraction