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Long video generation remains a challenging and compelling topic in computer vision. Diffusion based models, among the various approaches to video generation, have achieved state of the art quality with their iterative denoising procedures.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Siyang Zhang , Harry Yang , Ser-Nam Lim

Despite the existence of numerous colorization methods, several limitations still exist, such as lack of user interaction, inflexibility in local colorization, unnatural color rendering, insufficient color variation, and color overflow. To…

Computer Vision and Pattern Recognition · Computer Science 2024-02-19 Zhexin Liang , Zhaochen Li , Shangchen Zhou , Chongyi Li , Chen Change Loy

We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Tim Brooks , Janne Hellsten , Miika Aittala , Ting-Chun Wang , Timo Aila , Jaakko Lehtinen , Ming-Yu Liu , Alexei A. Efros , Tero Karras

Video inpainting aims to fill spatio-temporal "corrupted" regions with plausible content. To achieve this goal, it is necessary to find correspondences from neighbouring frames to faithfully hallucinate the unknown content. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2021-04-09 Xueyan Zou , Linjie Yang , Ding Liu , Yong Jae Lee

Consistency models have demonstrated powerful capability in efficient image generation and allowed synthesis within a few sampling steps, alleviating the high computational cost in diffusion models. However, the consistency model in the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Xiang Wang , Shiwei Zhang , Han Zhang , Yu Liu , Yingya Zhang , Changxin Gao , Nong Sang

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

Text-guided image editing has recently experienced rapid development. However, simultaneously performing multiple editing actions on a single image, such as background replacement and specific subject attribute changes, while maintaining…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Pengzhi Li , QInxuan Huang , Yikang Ding , Zhiheng Li

Applying an image processing algorithm independently to each video frame often leads to temporal inconsistency in the resulting video. To address this issue, we present a novel and general approach for blind video temporal consistency. Our…

Computer Vision and Pattern Recognition · Computer Science 2022-01-28 Chenyang Lei , Yazhou Xing , Hao Ouyang , Qifeng Chen

We present Stable Video Diffusion - a latent video diffusion model for high-resolution, state-of-the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained for 2D image synthesis have been turned into…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Andreas Blattmann , Tim Dockhorn , Sumith Kulal , Daniel Mendelevitch , Maciej Kilian , Dominik Lorenz , Yam Levi , Zion English , Vikram Voleti , Adam Letts , Varun Jampani , Robin Rombach

M3DDM provides a computationally efficient framework for video outpainting via latent diffusion modeling. However, it exhibits significant quality degradation -- manifested as spatial blur and temporal inconsistency -- under challenging…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Takuya Murakawa , Takumi Fukuzawa , Ning Ding , Toru Tamaki

In this paper, we investigate the problem of unpaired video-to-video translation. Given a video in the source domain, we aim to learn the conditional distribution of the corresponding video in the target domain, without seeing any pairs of…

Computer Vision and Pattern Recognition · Computer Science 2019-08-22 Kwanyong Park , Sanghyun Woo , Dahun Kim , Donghyeon Cho , In So Kweon

Diffusion models emerged as a leading approach in text-to-image generation, producing high-quality images from textual descriptions. However, attempting to achieve detailed control to get a desired image solely through text remains a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-12 Pablo Domingo-Gregorio , Javier Ruiz-Hidalgo

Real-world low-resolution (LR) videos have diverse and complex degradations, imposing great challenges on video super-resolution (VSR) algorithms to reproduce their high-resolution (HR) counterparts with high quality. Recently, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Xi Yang , Chenhang He , Jianqi Ma , Lei Zhang

Video editing and generation methods often rely on pre-trained image-based diffusion models. During the diffusion process, however, the reliance on rudimentary noise sampling techniques that do not preserve correlations present in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Pascal Chang , Jingwei Tang , Markus Gross , Vinicius C. Azevedo

How to effectively explore spatial-temporal features is important for video colorization. Instead of stacking multiple frames along the temporal dimension or recurrently propagating estimated features that will accumulate errors or cannot…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Yixin Yang , Jiangxin Dong , Jinhui Tang , Jinshan Pan

Given an input video of a person and a new garment, the objective of this paper is to synthesize a new video where the person is wearing the specified garment while maintaining spatiotemporal consistency. Although significant advances have…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Hung Nguyen , Quang Qui-Vinh Nguyen , Khoi Nguyen , Rang Nguyen

Diffusion Transformer(DiT)-based generation models have achieved remarkable success in video generation. However, their inherent computational demands pose significant efficiency challenges. In this paper, we exploit the inherent temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zhihang Yuan , Rui Xie , Yuzhang Shang , Hanling Zhang , Siyuan Wang , Shengen Yan , Guohao Dai , Yu Wang

Diffusion models have recently demonstrated their effectiveness in generating extremely high-quality images and are now utilized in a wide range of applications, including automatic sketch colorization. Although many methods have been…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Dingkun Yan , Liang Yuan , Erwin Wu , Yuma Nishioka , Issei Fujishiro , Suguru Saito

Image generation and editing have seen a great deal of advancements with the rise of large-scale diffusion models that allow user control of different modalities such as text, mask, depth maps, etc. However, controlled editing of videos…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 AmirHossein Zamani , Amir G. Aghdam , Tiberiu Popa , Eugene Belilovsky

Understanding videos requires more than answering open ended questions, it demands the ability to pinpoint when events occur and how entities interact across time. While recent Video LLMs have achieved remarkable progress in holistic…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Pengcheng Fang , Yuxia Chen , Rui Guo