3 papers
cs.CV2025
MotionSight: Boosting Fine-Grained Motion Understanding in Multimodal LLMs
Yipeng Du, Tiehan Fan, Kepan Nan +6
Despite advancements in Multimodal Large Language Models (MLLMs), their proficiency in fine-grained video motion understanding remains critically limited. They often lack inter-fra…
cs.CV2025
STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution
Rui Xie, Yinhong Liu, Penghao Zhou +7
Image diffusion models have been adapted for real-world video super-resolution to tackle over-smoothing issues in GAN-based methods. However, these models struggle to maintain temp…
cs.CV2024
InstanceCap: Improving Text-to-Video Generation via Instance-aware Structured Caption
Tiehan Fan, Kepan Nan, Rui Xie +6
Text-to-video generation has evolved rapidly in recent years, delivering remarkable results. Training typically relies on video-caption paired data, which plays a crucial role in e…