Brain-Inspired Low-Power Generative Model: A Review on Spiking Diffusion Models Background Overview In recent years, the artificial intelligence field has seen a surge in cutting-edge technologies, with deep generative models (DGMs) demonstrating exceptional capabilities in producing images, text, and other types of data. However, these generative ...

Dynamic People Tracking by Service Robots Using Diffusion Models Academic Background Tracking dynamic people in cluttered and crowded human-centered environments is a challenging problem in robotics. Due to intraclass variations such as occlusions, pose deformations, and lighting changes, traditional tracking methods often struggle to accurately id...

Academic Background and Problem Statement Story Visualization is a task aimed at generating a series of visually consistent images from a story described in text. This task requires the generated images to be of high quality, aligned with the text description, and consistent in character identities across different images. Despite its wide range of...

High-Quality Video Generation with Cascaded Latent Diffusion Models: LaVie Academic Background In recent years, with the breakthrough progress of Diffusion Models (DMs) in the field of image generation, Text-to-Image (T2I) generation technology has achieved significant success. However, extending this technology to Text-to-Video (T2V) generation st...

RaDiff: Controllable Diffusion Models for Radio Astronomical Map Generation” Comprehensive Academic News Analysis Background Introduction With the near completion of the Square Kilometer Array (SKA) telescope, radio astronomy is poised for revolutionary advancements in the study of the universe. Boasting unprecedented sensitivity and spatial resolu...