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Related papers: VISTA: Triplet-Supervised Video Style Transfer wit…

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Recent advancements in diffusion models have set new benchmarks in image and video generation, enabling realistic visual synthesis across single- and multi-frame contexts. However, these models still struggle with efficiently and explicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Qihang Zhang , Shuangfei Zhai , Miguel Angel Bautista , Kevin Miao , Alexander Toshev , Joshua Susskind , Jiatao Gu

Although diffusion-based zero-shot image restoration and enhancement methods have achieved great success, applying them to video restoration or enhancement will lead to severe temporal flickering. In this paper, we propose the first…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Cong Cao , Huanjing Yue , Shangbin Xie , Xin Liu , Jingyu Yang

While current research predominantly focuses on image-based colorization, the domain of video-based colorization remains relatively unexplored. Most existing video colorization techniques operate on a frame-by-frame basis, often overlooking…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Rory Ward , Dan Bigioi , Shubhajit Basak , John G. Breslin , Peter Corcoran

Video virtual try-on aims to generate realistic sequences that maintain garment identity and adapt to a person's pose and body shape in source videos. Traditional image-based methods, relying on warping and blending, struggle with complex…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Zijian He , Peixin Chen , Guangrun Wang , Guanbin Li , Philip H. S. Torr , Liang Lin

Virtual try-on aims to synthesize a realistic image of a person wearing a target garment, but accurately modeling garment-body correspondence remains a persistent challenge, especially under pose and appearance variation. In this paper, we…

Graphics · Computer Science 2025-11-06 Seungyong Lee , Jeong-gi Kwak

Modern text-to-video synthesis models demonstrate coherent, photorealistic generation of complex videos from a text description. However, most existing models lack fine-grained control over camera movement, which is critical for downstream…

Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior. However, applying these models to video super-resolution remains…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Shangchen Zhou , Peiqing Yang , Jianyi Wang , Yihang Luo , Chen Change Loy

Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very few works have done so for video editing. We present the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-03 Eyal Molad , Eliahu Horwitz , Dani Valevski , Alex Rav Acha , Yossi Matias , Yael Pritch , Yaniv Leviathan , Yedid Hoshen

We propose replacing scene text in videos using deep style transfer and learned photometric transformations.Building on recent progress on still image text replacement,we present extensions that alter text while preserving the appearance…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Vijay Kumar B G , Jeyasri Subramanian , Varnith Chordia , Eugene Bart , Shaobo Fang , Kelly Guan , Raja Bala

Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains constrained by severe inference costs. Compared with image generation, video synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Shitong Shao , Lichen Bai , Pengfei Wan , James Kwok , Zeke Xie

Portrait stylization, which translates a real human face image into an artistically stylized image, has attracted considerable interest and many prior works have shown impressive quality in recent years. However, despite their remarkable…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Doyeon Kim , Eunji Ko , Hyunsu Kim , Yunji Kim , Junho Kim , Dongchan Min , Junmo Kim , Sung Ju Hwang

Hairstyle transfer is a challenging task in the image editing field that modifies the hairstyle of a given face image while preserving its other appearance and background features. The existing hairstyle transfer approaches heavily rely on…

Computer Vision and Pattern Recognition · Computer Science 2024-12-23 Chaeyeon Chung , Sunghyun Park , Jeongho Kim , Jaegul Choo

Video generation has drawn significant interest recently, pushing the development of large-scale models capable of producing realistic videos with coherent motion. Due to memory constraints, these models typically generate short video…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Idan Kligvasser , Regev Cohen , George Leifman , Ehud Rivlin , Michael Elad

Image style transfer models based on convolutional neural networks usually suffer from high temporal inconsistency when applied to videos. Some video style transfer models have been proposed to improve temporal consistency, yet they fail to…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Chang Gao , Derun Gu , Fangjun Zhang , Yizhou Yu

Video try-on stands as a promising area for its tremendous real-world potential. Previous research on video try-on has primarily focused on transferring product clothing images to videos with simple human poses, while performing poorly with…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Jun Zheng , Jing Wang , Fuwei Zhao , Xujie Zhang , Xiaodan Liang

With the development of the convolutional neural network, image style transfer has drawn increasing attention. However, most existing approaches adopt a global feature transformation to transfer style patterns into content images (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2022-10-12 Jianbo Wang , Huan Yang , Jianlong Fu , Toshihiko Yamasaki , Baining Guo

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

Despite the recent advancement in video stylization, most existing methods struggle to render any video with complex transitions, based on an open style description of user query. To fill this gap, we introduce a generic multi-agent system…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Zhengrong Yue , Shaobin Zhuang , Kunchang Li , Yanbo Ding , Yali Wang

Despite the rapid advancement of Virtual Try-On (VTON) and Try-Off (VTOFF) technologies, existing VTON methods face challenges with fine-grained detail preservation, generalization to complex scenes, complicated pipeline, and efficient…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Weixuan Zeng , Pengcheng Wei , Huaiqing Wang , Boheng Zhang , Jia Sun , Dewen Fan , Lin HE , Long Chen , Qianqian Gan , Fan Yang , Tingting Gao

Text-to-video diffusion models have advanced video generation significantly. However, customizing these models to generate videos with tailored motions presents a substantial challenge. In specific, they encounter hurdles in (a) accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Hyeonho Jeong , Geon Yeong Park , Jong Chul Ye
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