Shuai Wan

Adjunct Professor Shuai Wan is affiliated with the School of Engineering at RMIT University (City Campus, Australia). His research focuses on computer vision, machine learning, 3D point cloud compression, neural video coding, and remote sensing. Key contributions include lightweight deep learning frameworks for image/video compression, spatio-temporal context models for point clouds, and adaptive quantization techniques.

Research Outputs Insights: Wan’s work spans 2024–2025, emphasizing end-to-end deep learning solutions for challenges in

• Exemplar-based colorization with semantic attention
• Rendering-oriented 3D point cloud compression
• Slimmable video codecs with variable bitrate
• G-PCC standard enhancements for quantization and entropy coding
• Adversarial example detection in remote sensing

Technical Domains: His articles intersect artificial intelligence, signal processing, and computer graphics, with applications in cloud gaming, SAR systems, and industrial data compression. Methods include transformers, attention networks, and 3D convolutional architectures.