3 papers
cs.AI2026
Navigating User Behavior toward Personalized Multimodal Generation
Hengji Zhou, Yufeng Liu, Ye Liu +3
Modern AIGC pipelines deliver high-fidelity images and videos but presuppose a well-formed creation instruction, while end users rarely articulate visual details, leaving generator…
cs.CV2025
MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators
Shenghai Yuan, Jinfa Huang, Yujun Shi +6
Recent advances in Text-to-Video generation (T2V) have achieved remarkable success in synthesizing high-quality general videos from textual descriptions. A largely overlooked probl…
cs.CV2024
ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation
Shenghai Yuan, Jinfa Huang, Yongqi Xu +7
We propose a novel text-to-video (T2V) generation benchmark, ChronoMagic-Bench, to evaluate the temporal and metamorphic capabilities of the T2V models (e.g. Sora and Lumiere) in t…