FilmWeaver: Weaving Consistent Multi-Shot Videos with Cache-Guided Autoregressive Diffusion
Xiangyang Luo, Qingyu Li, Xiaokun Liu, Wenyu Qin, Miao Yang, Meng Wang, Pengfei Wan, Di Zhang, Kun Gai, Shao-Lun Huang
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- FilmWeaver generates consistent multi-shot videos of arbitrary length via an autoregressive diffusion paradigm, enforcing inter-shot consistency with a Shot Cache and intra-shot coherence with a Temporal Cache, and supports applications such as concept injection and video extension.

Human Motion Video Generation: A Survey
Haiwei Xue, Xiangyang Luo, Zhanghao Hu, Xin Zhang, Xunzhi Xiang, Yuqin Dai, Jianzhuang Liu, Minglei Li, Jian Yang, Fei Ma, Changpeng Yang, Zonghong Dai, Fei Richard Yu
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- This survey provides a comprehensive review of human motion video generation methods, covering the latest techniques, applications, and future directions.

CanonSwap: High-Fidelity and Consistent Video Face Swapping via Canonical Space Modulation
Xiangyang Luo , Ye Zhu†, Yunfei Liu, Lijian Lin, Cong Wan, Zijian Cai, Shao-Lun Huang†, Yu Li
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- CanonSwap decouples motion information from appearance to enable high-fidelity and consistent video face swapping.

Grid: Omni Visual Generation
Cong Wan*, Xiangyang Luo*, Hao Luo, Zijian Cai, Yiren Song, Yunlong Zhao, Yifan Bai, Fan Wang, Yuhang He, Yihong Gong
PaperCode

- We introduces GRID, an omni-visual generation framework that reformulates temporal tasks like video into grid layouts, enabling a single powerful image model to efficiently handle image, video, and 3D generation.

Object Isolated Attention for Consistent Story Visualization
Xiangyang Luo, Junhao Cheng, Yifan Xie, Xin Zhang, Tao Feng, Zhou Liu, Fei Ma†, Fei Yu
Paper

- We proposes a training-free method that uses isolated attention mechanisms to maintain character consistency and prevent feature confusion in story visualization.

CodeSwap: Symmetrically Face Swapping Based on Prior Codebook
Xiangyang Luo, Xin Zhang, Yifan Xie, Xinyi Tong, Weijiang Yu, Heng Chang, Fei Ma†, Fei Ricahrd Yu
Paper

- CodeSwap achieves high-fidelity face swapping by symmetrically manipulating codes within a pre-trained, high-quality facial codebook.