Kinetograph: The Video Editing Technology Publication

Authors: (1) Xueying Mao, School of Computer Science, Fudan University, China (xymao22@[email protected]); (2) Xiaoxiao Hu, School of Computer Science, Fudan University, China ([email protected]); (3) Wanli Peng, School of Computer Science, Fudan University, China ([email protected]); (4) Zhenliang Gan, School of Computer Science, Fudan University, China (zlgan23@[email protected]); (5) Qichao Ying, School of Computer Science, Fudan University, China ([email protected]); (6) Zhenxing Qian, School of Computer Science, Fudan University, China and a Corresponding Author ([email protected]); (7) Sheng Li, School

Table of Links Abstract and 1. Introduction 2 Related Work 3 Preliminaries 4 Method 4.1 Key Sample and Joint Editing 4.2 Edit Propagation Via TokenFlow 5 Results 5.1 Qualitative Evaluation and 5.2 Quantitative Evaluation 5.3 Ablation Study 6 Discussion 7 Acknowledgement and References A Implementation Details ABSTRACT The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-the-art video models are still lagging behind image models in terms of visual quality and user control