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Related papers: Human Motion Video Generation: A Survey

200 papers

Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent motion generation methods can directly generate human motions…

Computer Vision and Pattern Recognition · Computer Science 2022-09-01 Mingyuan Zhang , Zhongang Cai , Liang Pan , Fangzhou Hong , Xinying Guo , Lei Yang , Ziwei Liu

Human-human motion generation is essential for understanding humans as social beings. Current methods fall into two main categories: single-person-based methods and separate modeling-based methods. To delve into this field, we abstract the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yabiao Wang , Shuo Wang , Jiangning Zhang , Ke Fan , Jiafu Wu , Zhucun Xue , Yong Liu

We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and…

Video generation models have recently achieved impressive visual fidelity and temporal coherence. Yet, they continue to struggle with complex, non-rigid motions, especially when synthesizing humans performing dynamic actions such as sports,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Kumar Ashutosh , XuDong Wang , Xi Yin , Kristen Grauman , Adam Polyak , Ishan Misra , Rohit Girdhar

Recent advancements in personalized Text-to-Video (T2V) generation have made significant strides in synthesizing character-specific content. However, these methods face a critical limitation: the inability to perform fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Haopeng Fang , Di Qiu , Binjie Mao , He Tang

The rapid expansion of video content across a variety of industries, including social media, education, entertainment, and surveillance, has made video summarization an essential field of study. The current work is a survey that explores…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Toqa Alaa , Ahmad Mongy , Assem Bakr , Mariam Diab , Walid Gomaa

Generating realistic human motion from given action descriptions has experienced significant advancements because of the emerging requirement of digital humans. While recent works have achieved impressive results in generating motion…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yaqi Zhang , Di Huang , Bin Liu , Shixiang Tang , Yan Lu , Lu Chen , Lei Bai , Qi Chu , Nenghai Yu , Wanli Ouyang

Human motion synthesis is a fundamental task in computer animation. Recent methods based on diffusion models or GPT structure demonstrate commendable performance but exhibit drawbacks in terms of slow sampling speeds and error accumulation.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Vincent Tao Hu , Wenzhe Yin , Pingchuan Ma , Yunlu Chen , Basura Fernando , Yuki M Asano , Efstratios Gavves , Pascal Mettes , Bjorn Ommer , Cees G. M. Snoek

Despite the significant progress that has been made in video generative models, existing state-of-the-art methods can only produce videos lasting 5-16 seconds, often labeled "long-form videos". Furthermore, videos exceeding 16 seconds…

In this paper, we introduce DirectorLLM, a novel video generation model that employs a large language model (LLM) to orchestrate human poses within videos. As foundational text-to-video models rapidly evolve, the demand for high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Kunpeng Song , Tingbo Hou , Zecheng He , Haoyu Ma , Jialiang Wang , Animesh Sinha , Sam Tsai , Yaqiao Luo , Xiaoliang Dai , Li Chen , Xide Xia , Peizhao Zhang , Peter Vajda , Ahmed Elgammal , Felix Juefei-Xu

We tackle the long video generation problem, i.e.~generating videos beyond the output length of video generation models. Due to the computation resource constraints, video generation models can only generate video clips that are relatively…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Hsin-Ping Huang , Yu-Chuan Su , Ming-Hsuan Yang

This paper offers an insightful examination of how currently top-trending AI technologies, i.e., generative artificial intelligence (Generative AI) and large language models (LLMs), are reshaping the field of video technology, including…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Pengyuan Zhou , Lin Wang , Zhi Liu , Yanbin Hao , Pan Hui , Sasu Tarkoma , Jussi Kangasharju

Deep generative models have unlocked another profound realm of human creativity. By capturing and generalizing patterns within data, we have entered the epoch of all-encompassing Artificial Intelligence for General Creativity (AIGC).…

Artificial Intelligence · Computer Science 2023-12-27 Hanqun Cao , Cheng Tan , Zhangyang Gao , Yilun Xu , Guangyong Chen , Pheng-Ann Heng , Stan Z. Li

Current approaches to video analysis of human motion focus on raw pixels or keypoints as the basic units of reasoning. We posit that adding higher-level motion primitives, which can capture natural coarser units of motion such as backswing…

Computer Vision and Pattern Recognition · Computer Science 2021-04-23 Sumith Kulal , Jiayuan Mao , Alex Aiken , Jiajun Wu

Image and video synthesis are closely related areas aiming at generating content from noise. While rapid progress has been demonstrated in improving image-based models to handle large resolutions, high-quality renderings, and wide…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Yu Tian , Jian Ren , Menglei Chai , Kyle Olszewski , Xi Peng , Dimitris N. Metaxas , Sergey Tulyakov

Diffusion models have emerged as a widely utilized and successful methodology in human motion synthesis. Task-oriented diffusion models have significantly advanced action-to-motion, text-to-motion, and audio-to-motion applications. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Yuduo Jin , Brandon Haworth

In recent years, artificial intelligence (AI) has made significant progress in the field of music generation, driving innovation in music creation and applications. This paper provides a systematic review of the latest research advancements…

Sound · Computer Science 2024-09-06 Yanxu Chen , Linshu Huang , Tian Gou

Co-speech gestures, if presented in the lively form of videos, can achieve superior visual effects in human-machine interaction. While previous works mostly generate structural human skeletons, resulting in the omission of appearance…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xu He , Qiaochu Huang , Zhensong Zhang , Zhiwei Lin , Zhiyong Wu , Sicheng Yang , Minglei Li , Zhiyi Chen , Songcen Xu , Xiaofei Wu

Video generation is experiencing rapid growth, driven by advances in diffusion models and the development of better and larger datasets. However, producing high-quality videos remains challenging due to the high-dimensional data and the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Elia Peruzzo , Dejia Xu , Xingqian Xu , Humphrey Shi , Nicu Sebe

Image animation has become a promising area in multimodal research, with a focus on generating videos from reference images. While prior work has largely emphasized generic video generation guided by text, music-driven dance video…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Zhikang Dong , Weituo Hao , Ju-Chiang Wang , Peng Zhang , Pawel Polak