5 papers
FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation
Xinhang Yuan, Zexi Huang, Anjia Cao +6
Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates collaborative signals from user inte…
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…
OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation
Kepan Nan, Rui Xie, Penghao Zhou +6
Text-to-video (T2V) generation has recently garnered significant attention thanks to the large multi-modality model Sora. However, T2V generation still faces two important challeng…
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…
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…