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Image diffusion models, trained on massive image collections, have emerged as the most versatile image generator model in terms of quality and diversity. They support inverting real images and conditional (e.g., text) generation, making…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Duygu Ceylan , Chun-Hao Paul Huang , Niloy J. Mitra

While text-to-video diffusion models have made significant strides, many still face challenges in generating videos with temporal consistency. Within diffusion frameworks, guidance techniques have proven effective in enhancing output…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Hyelin Nam , Jaemin Kim , Dohun Lee , Jong Chul Ye

Large pretrained diffusion models have significantly enhanced the quality of generated videos, and yet their use in real-time streaming remains limited. Autoregressive models offer a natural framework for sequential frame synthesis but…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Jinxiu Liu , Xuanming Liu , Kangfu Mei , Yandong Wen , Ming-Hsuan Yang , Weiyang Liu

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

In this study, we propose a method for video face reenactment that integrates a 3D face parametric model into a latent diffusion framework, aiming to improve shape consistency and motion control in existing video-based face generation…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Mengting Wei , Yante Li , Tuomas Varanka , Yan Jiang , Guoying Zhao

Diffusion models have emerged as a powerful generative method for synthesizing high-quality and diverse set of images. In this paper, we propose a video generation method based on diffusion models, where the effects of motion are modeled in…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Kangfu Mei , Vishal M. Patel

Video editing is a challenging task that requires manipulating videos on both the spatial and temporal dimensions. Existing methods for video editing mainly focus on changing the appearance or style of the objects in the video, while…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Yao Teng , Enze Xie , Yue Wu , Haoyu Han , Zhenguo Li , Xihui Liu

We present an efficient text-to-video generation framework based on latent diffusion models, termed MagicVideo. MagicVideo can generate smooth video clips that are concordant with the given text descriptions. Due to a novel and efficient 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Daquan Zhou , Weimin Wang , Hanshu Yan , Weiwei Lv , Yizhe Zhu , Jiashi Feng

Recently, diffusion models like StableDiffusion have achieved impressive image generation results. However, the generation process of such diffusion models is uncontrollable, which makes it hard to generate videos with continuous and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Zhihao Hu , Dong Xu

Text-based video editing has recently attracted considerable interest in changing the style or replacing the objects with a similar structure. Beyond this, we demonstrate that properties such as shape, size, location, motion, etc., can also…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Yue Ma , Xiaodong Cun , Sen Liang , Jinbo Xing , Yingqing He , Chenyang Qi , Siran Chen , Qifeng Chen

Benefiting from the rapid development of 2D diffusion models, 3D content generation has witnessed significant progress. One promising solution is to finetune the pre-trained 2D diffusion models to produce multi-view images and then…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Fan Yang , Jianfeng Zhang , Yichun Shi , Bowen Chen , Chenxu Zhang , Huichao Zhang , Xiaofeng Yang , Xiu Li , Jiashi Feng , Guosheng Lin

The video generation field has witnessed rapid improvements with the introduction of recent diffusion models. While these models have successfully enhanced appearance quality, they still face challenges in generating coherent and natural…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Yaosi Hu , Zhenzhong Chen , Chong Luo

Propagation-based video editing enables precise user control by propagating a single edited frame into following frames while maintaining the original context such as motion and structures. However, training such models requires…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Wonyong Seo , Jaeho Moon , Jaehyup Lee , Soo Ye Kim , Munchurl Kim

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

In this work, we address a challenge in video inpainting: reconstructing occluded regions in dynamic, real-world scenarios. Motivated by the need for continuous human motion monitoring in healthcare settings, where facial features are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zheyan Zhang , Diego Klabjan , Renee CB Manworren

Inspired by the impressive performance of recent face image editing methods, several studies have been naturally proposed to extend these methods to the face video editing task. One of the main challenges here is temporal consistency among…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Gyeongman Kim , Hajin Shim , Hyunsu Kim , Yunjey Choi , Junho Kim , Eunho Yang

Real-time character control is an essential component for interactive experiences, with a broad range of applications, including physics simulations, video games, and virtual reality. The success of diffusion models for image synthesis has…

Computer Vision and Pattern Recognition · Computer Science 2024-08-19 Yi Shi , Jingbo Wang , Xuekun Jiang , Bingkun Lin , Bo Dai , Xue Bin Peng

In this paper, we study the problem of procedure planning in instructional videos, which aims to make a plan (i.e. a sequence of actions) given the current visual observation and the desired goal. Previous works cast this as a sequence…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Hanlin Wang , Yilu Wu , Sheng Guo , Limin Wang

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

Despite impressive advancements in diffusion-based video editing models in altering video attributes, there has been limited exploration into modifying motion information while preserving the original protagonist's appearance and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Shuyuan Tu , Qi Dai , Zihao Zhang , Sicheng Xie , Zhi-Qi Cheng , Chong Luo , Xintong Han , Zuxuan Wu , Yu-Gang Jiang