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Related papers: DreamStyle: A Unified Framework for Video Stylizat…

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3D scene stylization refers to transform the appearance of a 3D scene to match a given style image, ensuring that images rendered from different viewpoints exhibit the same style as the given style image, while maintaining the 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Jiafu Chen , Wei Xing , Jiakai Sun , Tianyi Chu , Yiling Huang , Boyan Ji , Lei Zhao , Huaizhong Lin , Haibo Chen , Zhizhong Wang

Text-driven style transfer aims to merge the style of a reference image with content described by a text prompt. Recent advancements in text-to-image models have improved the nuance of style transformations, yet significant challenges…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Mingkun Lei , Xue Song , Beier Zhu , Hao Wang , Chi Zhang

Previous text-to-image synthesis algorithms typically use explicit textual instructions to generate/manipulate images accurately, but they have difficulty adapting to guidance in the form of coarsely matched texts. In this work, we attempt…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Mengyao Cui , Zhe Zhu , Shao-Ping Lu , Yulu Yang

The success of 3DGS in generative and editing applications has sparked growing interest in 3DGS-based style transfer. However, current methods still face two major challenges: (1) multi-view inconsistency often leads to style conflicts,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Yitong Yang , Yinglin Wang , Changshuo Wang , Huajie Wang , Shuting He

Video frame interpolation aims to synthesize realistic intermediate frames between given endpoints while adhering to specific motion semantics. While recent generative models have improved visual fidelity, they predominantly operate in a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Lingyu Liu , Yaxiong Wang , Li Zhu , Zhedong Zheng

With the availability of large-scale video datasets and the advances of diffusion models, text-driven video generation has achieved substantial progress. However, existing video generation models are typically trained on a limited number of…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Haonan Qiu , Menghan Xia , Yong Zhang , Yingqing He , Xintao Wang , Ying Shan , Ziwei Liu

This paper presents \emph{ControlVideo} for text-driven video editing -- generating a video that aligns with a given text while preserving the structure of the source video. Building on a pre-trained text-to-image diffusion model,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Min Zhao , Rongzhen Wang , Fan Bao , Chongxuan Li , Jun Zhu

Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regularization or feed-forward deterministic model) to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hanyang Wang , Fangfu Liu , Jiawei Chi , Yueqi Duan

Recent progress has shown that video diffusion models (VDMs) can be repurposed for diverse multimodal graphics tasks. However, existing methods often train separate models for each problem setting, which fixes the input-output mapping and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Houyuan Chen , Hong Li , Xianghao Kong , Tianrui Zhu , Shaocong Xu , Weiqing Xiao , Yuwei Guo , Chongjie Ye , Lvmin Zhang , Hao Zhao , Anyi Rao

Customized text-to-video generation aims to generate high-quality videos guided by text prompts and subject references. Current approaches for personalizing text-to-video generation suffer from tackling multiple subjects, which is a more…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Zhao Wang , Aoxue Li , Lingting Zhu , Yong Guo , Qi Dou , Zhenguo Li

Despite the fact that text-to-video (TTV) model has recently achieved remarkable success, there have been few approaches on TTV for its extension to video editing. Motivated by approaches on TTV models adapting from diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Chaehun Shin , Heeseung Kim , Che Hyun Lee , Sang-gil Lee , Sungroh Yoon

We present a new dataset with the goal of advancing image style transfer - the task of rendering one image in the style of another image. The dataset covers various content and style images of different size and contains 10.000 stylizations…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Victor Kitov , Valentin Abramov , Mikhail Akhtyrchenko

Generating images in a consistent reference visual style remains a challenging computer vision task. State-of-the-art methods aiming for style-consistent generation struggle to effectively separate semantic content from stylistic elements,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Tilemachos Aravanis , Panagiotis Filntisis , Petros Maragos , George Retsinas

In this work, we aim to address the 3D scene stylization problem - generating stylized images of the scene at arbitrary novel view angles. A straightforward solution is to combine existing novel view synthesis and image/video style transfer…

Computer Vision and Pattern Recognition · Computer Science 2022-01-19 Pei-Ze Chiang , Meng-Shiun Tsai , Hung-Yu Tseng , Wei-sheng Lai , Wei-Chen Chiu

Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of text-to-4D dynamic 3D scene generation with diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Yufeng Zheng , Xueting Li , Koki Nagano , Sifei Liu , Karsten Kreis , Otmar Hilliges , Shalini De Mello

Diffusion models have recently emerged as powerful tools for camera simulation, enabling both geometric transformations and realistic optical effects. Among these, image-based bokeh rendering has shown promising results, but diffusion for…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yang Yang , Siming Zheng , Qirui Yang , Jinwei Chen , Boxi Wu , Xiaofei He , Deng Cai , Bo Li , Peng-Tao Jiang

The task of video virtual try-on aims to fit the target clothes to a person in the video with spatio-temporal consistency. Despite tremendous progress of image virtual try-on, they lead to inconsistency between frames when applied to…

Computer Vision and Pattern Recognition · Computer Science 2022-04-27 Jianbin Jiang , Tan Wang , He Yan , Junhui Liu

Linguistic style is an essential part of written communication, with the power to affect both clarity and attractiveness. With recent advances in vision and language, we can start to tackle the problem of generating image captions that are…

Computer Vision and Pattern Recognition · Computer Science 2018-05-21 Alexander Mathews , Lexing Xie , Xuming He

In this paper, we present a new text-guided 3D shape generation approach DreamStone that uses images as a stepping stone to bridge the gap between text and shape modalities for generating 3D shapes without requiring paired text and 3D data.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Zhengzhe Liu , Peng Dai , Ruihui Li , Xiaojuan Qi , Chi-Wing Fu

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet