1 citations · 1 across the 7 of their papers we have counts for
7 papers
VC4VG: Optimizing Video Captions for Text-to-Video Generation
Yang Du, Zhuoran Lin, Kaiqiang Song +5
Recent advances in text-to-video (T2V) generation highlight the critical role of high-quality video-text pairs in training models capable of producing coherent and instruction-alig…
Identity-Preserving Image-to-Video Generation via Reward-Guided Optimization
Liao Shen, Wentao Jiang, Yiran Zhu +4
Recent advances in image-to-video (I2V) generation have achieved remarkable progress in synthesizing high-quality, temporally coherent videos from static images. Among all the appl…
Discovering "Words" in Music: Unsupervised Learning of Compositional Sparse Code for Symbolic Music
Tianle Wang, Sirui Zhang, Xinyi Tong +12
This paper presents an unsupervised machine learning algorithm that identifies recurring patterns -- referred to as ``music-words'' -- from symbolic music data. These patterns are…
Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and Insights
Xiang-Rong Sheng, Feifan Yang, Litong Gong +10
Despite the recognized potential of multimodal data to improve model accuracy, many large-scale industrial recommendation systems, including Taobao display advertising system, pred…
Synchronized Video Storytelling: Generating Video Narrations with Structured Storyline
Dingyi Yang, Chunru Zhan, Ziheng Wang +4
Video storytelling is engaging multimedia content that utilizes video and its accompanying narration to attract the audience, where a key challenge is creating narrations for recor…
Tuning-Free Noise Rectification for High Fidelity Image-to-Video Generation
Weijie Li, Litong Gong, Yiran Zhu +4
Image-to-video (I2V) generation tasks always suffer from keeping high fidelity in the open domains. Traditional image animation techniques primarily focus on specific domains such…
AtomoVideo: High Fidelity Image-to-Video Generation
Litong Gong, Yiran Zhu, Weijie Li +4
Recently, video generation has achieved significant rapid development based on superior text-to-image generation techniques. In this work, we propose a high fidelity framework for…