Blending Method

Blending methods encompass techniques for seamlessly integrating diverse data sources or representations, aiming to leverage the strengths of each component while mitigating weaknesses. Current research focuses on applications across various domains, including image and video editing (using diffusion models and NeRFs), time series generation (employing vector quantization and self-supervised learning), and multimodal data fusion (integrating text, numerical data, and visual information within LLMs). These advancements improve the quality and realism of generated content, enhance the accuracy and interpretability of models, and enable more sophisticated analysis of complex datasets, impacting fields from computer vision and AI to signal processing and data analytics.