Autoregressive video generation is a rapidly evolving research domain. It focuses on the synthesis of videos frame-by-frame using learned patterns of both spatial arrangements and temporal dynamics. Unlike traditional video creation methods, which may rely on pre-built frames or handcrafted transitions, autoregressive models aim to generate content dynamically based on prior tokens. This approach is…

Vision-language models (VLMs) play a crucial role in today’s intelligent systems by enabling a detailed understanding of visual content. The complexity of multimodal intelligence tasks has grown, ranging from scientific problem-solving to the development of autonomous agents. Current demands on VLMs have far exceeded simple visual content perception, with increasing attention on advanced reasoning. While…

Understanding the Link Between Body Movement and Visual Perception The study of human visual perception through egocentric views is crucial in developing intelligent systems capable of understanding & interacting with their environment. This area emphasizes how movements of the human body—ranging from locomotion to arm manipulation—shape what is seen from a first-person perspective. Understanding this…