3 papers
cs.CV2026
MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation
Haojie Zhang, Di Wu, Bingyan Liu +5
While video foundation models excel at single-shot generation, real-world cinematic storytelling inherently relies on complex multi-shot sequencing. Further progress is constrained…
cs.CV2025
Encapsulated Composition of Text-to-Image and Text-to-Video Models for High-Quality Video Synthesis
Tongtong Su, Chengyu Wang, Bingyan Liu +2
In recent years, large text-to-video (T2V) synthesis models have garnered considerable attention for their abilities to generate videos from textual descriptions. However, achievin…
cs.CV2025
Understanding Attention Mechanism in Video Diffusion Models
Bingyan Liu, Chengyu Wang, Tongtong Su +4
Text-to-video (T2V) synthesis models, such as OpenAI's Sora, have garnered significant attention due to their ability to generate high-quality videos from a text prompt. In diffusi…