Visual Data Compression in the AI Era

This talk will delve into the evolution of visual data compression in recent years, spotlighting how compression techniques and AI models are integrated together. Traditionally, image and video codecs such as JPEG, HEVC, and AV1 are designed primarily for accurate pixel reconstruction. However, the advancement of AI technologies has begun transforming these frameworks to meet modern application demands. This talk will discuss such shift through three lenses: - Compression with AI: enhance the coding performance of compression algorithms with AI techniques. I will discuss the use of generative AI models, particularly variational autoencoders in lossy image compression, and their resemblance to traditional coding concepts such as transform coding, and wavelet transform. - Compression for AI: design compression systems for AI-based recognition and processing (as opposed to human viewing only). I will showcase potential real-world applications of coding for machines and present several recent methods targeting mobile-cloud systems. - Compression of AI: efficient compression of AI models to reduce computational costs. I will present pruning and quantization methods to address the challenges of compressing neural network-based codecs.