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In this paper, we propose a novel framework for solving high-definition video inverse problems using latent image diffusion models. Building on recent advancements in spatio-temporal optimization for video inverse problems using image…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Taesung Kwon , Jong Chul Ye

In this paper, we propose the first diffusion-based all-in-one video restoration method that utilizes the power of a pre-trained Stable Diffusion and a fine-tuned ControlNet. Our method can restore various types of video degradation with a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Yizhou Li , Zihua Liu , Yusuke Monno , Masatoshi Okutomi

Images produced by text-to-image diffusion models might not always faithfully represent the semantic intent of the provided text prompt, where the model might overlook or entirely fail to produce certain objects. Existing solutions often…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Tuna Han Salih Meral , Enis Simsar , Federico Tombari , Pinar Yanardag

Diffusion models have shown great results in image generation and in image editing. However, current approaches are limited to low resolutions due to the computational cost of training diffusion models for high-resolution generation. We…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Johannes Ackermann , Minjun Li

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

As 3D generation techniques continue to flourish, the demand for generating personalized content is rapidly rising. Users increasingly seek to apply various editing methods to polish generated 3D content, aiming to enhance its color, style,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Weitao Wang , Haoran Xu , Jun Meng , Haoqian Wang

Diffusion-based video editing have reached impressive quality and can transform either the global style, local structure, and attributes of given video inputs, following textual edit prompts. However, such solutions typically incur heavy…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Kumara Kahatapitiya , Adil Karjauv , Davide Abati , Fatih Porikli , Yuki M. Asano , Amirhossein Habibian

Diffusion-based text-to-image generative models, e.g., Stable Diffusion, have revolutionized the field of content generation, enabling significant advancements in areas like image editing and video synthesis. Despite their formidable…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Yanyu Li , Xian Liu , Anil Kag , Ju Hu , Yerlan Idelbayev , Dhritiman Sagar , Yanzhi Wang , Sergey Tulyakov , Jian Ren

Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering high-quality, spatially consistent new views. While recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Jeong-gi Kwak , Erqun Dong , Yuhe Jin , Hanseok Ko , Shweta Mahajan , Kwang Moo Yi

The field of visual computing is rapidly advancing due to the emergence of generative artificial intelligence (AI), which unlocks unprecedented capabilities for the generation, editing, and reconstruction of images, videos, and 3D scenes.…

In this work, we investigate the capability of generating images from pre-trained diffusion models at much higher resolutions than the training image sizes. In addition, the generated images should have arbitrary image aspect ratios. When…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Yingqing He , Shaoshu Yang , Haoxin Chen , Xiaodong Cun , Menghan Xia , Yong Zhang , Xintao Wang , Ran He , Qifeng Chen , Ying Shan

We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution (SR). Specifically, by employing our time-aware encoder, we can achieve promising restoration…

Computer Vision and Pattern Recognition · Computer Science 2024-07-01 Jianyi Wang , Zongsheng Yue , Shangchen Zhou , Kelvin C. K. Chan , Chen Change Loy

We present a diffusion-based video editing framework, namely DiffusionAtlas, which can achieve both frame consistency and high fidelity in editing video object appearance. Despite the success in image editing, diffusion models still…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Shao-Yu Chang , Hwann-Tzong Chen , Tyng-Luh Liu

Image stitching from different captures often results in non-rectangular boundaries, which is often considered unappealing. To solve non-rectangular boundaries, current solutions involve cropping, which discards image content, inpainting,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Tianhao Zhou , Haipeng Li , Ziyi Wang , Ao Luo , Chen-Lin Zhang , Jiajun Li , Bing Zeng , Shuaicheng Liu

For recent diffusion-based generative models, maintaining consistent content across a series of generated images, especially those containing subjects and complex details, presents a significant challenge. In this paper, we propose a new…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yupeng Zhou , Daquan Zhou , Ming-Ming Cheng , Jiashi Feng , Qibin Hou

Neural Style Transfer (NST) is the field of study applying neural techniques to modify the artistic appearance of a content image to match the style of a reference style image. Traditionally, NST methods have focused on texture-based image…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Dan Ruta , Gemma Canet Tarrés , Andrew Gilbert , Eli Shechtman , Nicholas Kolkin , John Collomosse

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Duolikun Danier , Ge Gao , Steven McDonagh , Changjian Li , Hakan Bilen , Oisin Mac Aodha

Urban renewal and transformation processes necessitate the preservation of the historical urban fabric, particularly in districts known for their architectural and historical significance. These regions, with their diverse architectural…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Zheyuan Kuang , Jiaxin Zhang , Yiying Huang , Yunqin Li

The reconstruction of low-resolution football broadcast images presents a significant challenge in sports broadcasting, where detailed visuals are essential for analysis and audience engagement. This study introduces a multi-stage…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Luca Martini , Daniele Zolezzi , Saverio Iacono , Gianni Viardo Vercelli

Portrait animation aims to generate photo-realistic videos from a single source image by reenacting the expression and pose from a driving video. While early methods relied on 3D morphable models or feature warping techniques, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mallikarjun B. R. , Fei Yin , Vikram Voleti , Nikita Drobyshev , Maksim Lapin , Aaryaman Vasishta , Varun Jampani