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Related papers: A Survey on Video Diffusion Models

200 papers

Transition videos play a crucial role in media production, enhancing the flow and coherence of visual narratives. Traditional methods like morphing often lack artistic appeal and require specialized skills, limiting their effectiveness.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Rui Zhang , Yaosen Chen , Yuegen Liu , Wei Wang , Xuming Wen , Hongxia Wang

The diffusion model has recently emerged as a potent approach in computer vision, demonstrating remarkable performances in the field of generative artificial intelligence. Capable of producing high-quality synthetic images, diffusion models…

Image and Video Processing · Electrical Eng. & Systems 2025-05-14 Abdullah , Tao Huang , Ickjai Lee , Euijoon Ahn

Video generation primarily aims to model authentic and customized motion across frames, making understanding and controlling the motion a crucial topic. Most diffusion-based studies on video motion focus on motion customization with…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zeqi Xiao , Yifan Zhou , Shuai Yang , Xingang Pan

Recent years have seen remarkable progress in both multimodal understanding models and image generation models. Despite their respective successes, these two domains have evolved independently, leading to distinct architectural paradigms:…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Shanshan Zhao , Xinjie Zhang , Jintao Guo , Jiakui Hu , Lunhao Duan , Minghao Fu , Yong Xien Chng , Guo-Hua Wang , Qing-Guo Chen , Zhao Xu , Weihua Luo , Kaifu Zhang

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

Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeling and encounter challenges in integrating diverse prior…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiyu Zhang , Xinyuan Chen , Yaohui Wang , Xihui Liu , Yunhong Wang , Yu Qiao

Diffusion-based generative modeling has been achieving state-of-the-art results on various generation tasks. Most diffusion models, however, are limited to a single-generation modeling. Can we generalize diffusion models with the ability of…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Changyou Chen , Han Ding , Bunyamin Sisman , Yi Xu , Ouye Xie , Benjamin Z. Yao , Son Dinh Tran , Belinda Zeng

Generative AI (GenAI) is transforming filmmaking, equipping artists with tools like text-to-image and image-to-video diffusion, neural radiance fields, avatar generation, and 3D synthesis. This paper examines the adoption of these…

AI-Generated Content (AIGC), as a novel manner of providing Metaverse services in the forthcoming Internet paradigm, can resolve the obstacles of immersion requirements. Concurrently, edge computing, as an evolutionary paradigm of computing…

Artificial Intelligence · Computer Science 2024-03-26 Yitong Wang , Chang Liu , Jun Zhao

Diffusion models have achieved significant success in image and video generation. This motivates a growing interest in video editing tasks, where videos are edited according to provided text descriptions. However, most existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Zhen Xing , Qi Dai , Zihao Zhang , Hui Zhang , Han Hu , Zuxuan Wu , Yu-Gang Jiang

World modeling has become a cornerstone in AI research, enabling agents to understand, represent, and predict the dynamic environments they inhabit. While prior work largely emphasizes generative methods for 2D image and video data, they…

Being the most cutting-edge generative methods, diffusion methods have shown great advances in wide generation tasks. Among them, graph generation attracts significant research attention for its broad application in real life. In our…

Machine Learning · Computer Science 2024-07-17 Hongyang Chen , Can Xu , Lingyu Zheng , Qiang Zhang , Xuemin Lin

Recent advances in generative AI have significantly enhanced image and video editing, particularly in the context of text prompt control. State-of-the-art approaches predominantly rely on diffusion models to accomplish these tasks. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Haoyu Ma , Shahin Mahdizadehaghdam , Bichen Wu , Zhipeng Fan , Yuchao Gu , Wenliang Zhao , Lior Shapira , Xiaohui Xie

A diffusion probabilistic model (DPM), which constructs a forward diffusion process by gradually adding noise to data points and learns the reverse denoising process to generate new samples, has been shown to handle complex data…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Zhengxiong Luo , Dayou Chen , Yingya Zhang , Yan Huang , Liang Wang , Yujun Shen , Deli Zhao , Jingren Zhou , Tieniu Tan

Video generation has achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent research has primarily focused on scaling up model training,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Chenyang Si , Weichen Fan , Zhengyao Lv , Ziqi Huang , Yu Qiao , Ziwei Liu

Large-scale generative models have achieved remarkable success in a number of domains. However, for sequential decision-making problems, such as robotics, action-labelled data is often scarce and therefore scaling-up foundation models for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Marc Rigter , Tarun Gupta , Agrin Hilmkil , Chao Ma

In recent years, deep learning based generative models, particularly Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models (DMs), have been instrumental in in generating diverse, high-quality content…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Shamim Yazdani , Akansha Singh , Nripsuta Saxena , Zichong Wang , Avash Palikhe , Deng Pan , Umapada Pal , Jie Yang , Wenbin Zhang

The rapid advancement of Artificial Intelligence (AI) has catalyzed revolutionary changes across various sectors, notably in healthcare. In particular, generative AI-led by diffusion models and transformer architectures-has enabled…

Generative AI is transforming image synthesis, enabling the creation of high-quality, diverse, and photorealistic visuals across industries like design, media, healthcare, and autonomous systems. Advances in techniques such as…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Fouad Bousetouane

Video diffusion models are able to generate high-quality videos by learning strong spatial-temporal priors on large-scale datasets. In this paper, we aim to investigate whether such priors derived from a generative process are suitable for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zejia Weng , Xitong Yang , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang