Image customization has been extensively studied in text-to-image (T2I) diffusion models, leading to impressive outcomes and applications. With the emergence of text-to-video (T2V) diffusion models, its temporal counterpart, motion customization, has not yet been well investigated. To address the challenge of one-shot video motion customization, we propose Customize-A-Video that models the motion from a single reference video and adapts it to new subjects and scenes with both spatial and temporal varieties. It leverages low-rank adaptation (LoRA) on temporal attention layers to tailor the pre-trained T2V diffusion model for specific motion modeling. To disentangle the spatial and temporal information during training, we introduce a novel concept of appearance absorbers that detach the original appearance from the reference video prior to motion learning. The proposed modules are trained in a staged pipeline and inferred in a plug-and-play fashion, enabling easy extensions to various downstream tasks such as custom video generation and editing, video appearance customization and multiple motion combination. Our project page can be found at https://customize-a-video.github.io.
Diff-PC: Identity-preserving and 3D-aware Controllable Diffusion for Zero-shot Portrait Customization
School of Electronic Science and Engineering, Nanjing University（南京大学电子科学与工程学院）；School of Business, Hohai University（河海大学商学院）；School of Artificial Intelligence, Nanjing University of Information Science and Technology（南京信息工程大学人工智能学院）
FaceSnap: Enhanced ID-fidelity Network for Tuning-free Portrait Customization
Vision AI System Lab, Nanjing University, Nanjing, China（南京大学视觉人工智能系统实验室）；Research and Development Department, Wonxing Technology, Shanghai, China（Wonxing技术有限公司研发部）
MotionCrafter: One-Shot Motion Customization of Diffusion Models
MAIS, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所多模态人工智能系统全国重点实验室）；School of AI, UCAS（中国科学院大学人工智能学院）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；Kuaishou Technology（快手科技）
OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions
Johns Hopkins University（约翰霍普金斯大学）；Adobe Research（Adobe研究）；The University of Hong Kong（香港大学）；The Chinese University of Hong Kong（香港中文大学）；Shanghai Jiao Tong University（上海交通大学）
VideoMaker: Zero-shot Customized Video Generation with the Inherent Force of Video Diffusion Models
College of Computer Science and Technology, Zhejiang University（浙江大学计算机科学与技术学院）；ARC Lab, Tencent PCG（腾讯平台与内容事业群ARC实验室）；Tencent AI Lab（腾讯AI实验室）；Huawei Noah’s Ark Lab（华为诺亚方舟实验室）
Multi-party Collaborative Attention Control for Image Customization
Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Department of Radiology, The First Affiliated Hospital of Army Medical University（中国人民解放军军医大学第一附属医院放射科）
MuseumMaker: Continual Style Customization without Catastrophic Forgetting
State Key Laboratory of Robotics, the Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences（中国科学院机器人与智能制造研究院机器人国家重点实验室）；University of Chinese Academy of Sciences（中国科学院大学）；School of Automation Science and Engineering, South China University of Technology（华南理工大学自动化科学与工程学院）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Salesforce AI Research（Salesforce AI研究部门）
JointTuner: Appearance-Motion Adaptive Joint Training for Customized Video Generation
College of Computer Science and Technology, National University of Defense Technology（计算机科学与技术学院，国防科技大学）；Alibaba International Digital Commerce（阿里巴巴国际数字商业）
MotionAdapter: Video Motion Transfer via Content-Aware Attention Customization
Hangzhou Dianzi University（杭州电子科技大学）；Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））；The Hong Kong University of Science and Technology（香港科技大学）；Ocean University of China（中国海洋大学）；Singapore Management University（新加坡管理大学）
CusEnhancer: A Zero-Shot Scene and Controllability Enhancement Method for Photo Customization via ResInversion
College of Computer Science and Technology, East China University of Science and Technology（计算机科学与技术学院，东华大学）；Carnegie Mellon University（卡内基梅隆大学）；Microsoft（微软公司）
VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning on Language-Video Foundation Models
Tsinghua University（清华大学）；Beijing National Research Center for Information Science and Technology（北京信息科学与技术国家研究中心）；Beijing Film Academy（北京电影学院）；Beijing University of Technology（北京工业大学）
CustomTTT: Motion and Appearance Customized Video Generation via Test-Time Training
Chongqing University of Posts and Telecommunications（重庆邮电大学）；Great Bay University（大湾区大学）；Meituan（美团）；Jinan Inspur Data Technology Co., Ltd.（济南浪潮数据技术有限公司）
