Xin Li

Title: Xin Li - Innovator in Vector-Quantized Image Modeling

Introduction

Xin Li is an accomplished inventor based in Santa Clara, CA (US). She is currently associated with Keysight Technologies Singapore Pte. Ltd. Despite having no granted patents, her contributions to the field of image modeling are noteworthy.

Latest Patent Applications

Xin Li's latest patent application is titled "Vector-Quantized Image Modeling." This application presents systems and methods for vector-quantized image modeling using vision transformers and improved codebook handling. The disclosure outlines a Vector-Quantized Image Modeling (VIM) approach that involves pre-training a machine learning model, such as a Transformer model, to predict rasterized image tokens autoregressively. The discrete image tokens can be encoded from a learned Vision-Transformer-based VQGAN, referred to as ViT-VQGAN. The application proposes multiple improvements over vanilla VQGAN, enhancing architecture and codebook learning, which leads to better efficiency and reconstruction fidelity. The improved ViT-VQGAN further advances vector-quantized image modeling tasks, including unconditional image generation, conditioned image generation, and unsupervised representation learning.

Conclusion

Xin Li's innovative work in vector-quantized image modeling showcases her expertise and potential impact in the field of machine learning and image processing. Her contributions are paving the way for advancements in technology and research.