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Recent advancements in leveraging pre-trained 2D diffusion models achieve the generation of high-quality novel views from a single in-the-wild image. However, existing works face challenges in producing controllable novel views due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Yunhan Yang , Shuo Chen , Yukun Huang , Xiaoyang Wu , Yuan-Chen Guo , Edmund Y. Lam , Hengshuang Zhao , Tong He , Xihui Liu

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

Layers have become indispensable tools for professional artists, allowing them to build a hierarchical structure that enables independent control over individual visual elements. In this paper, we propose LayeringDiff, a novel pipeline for…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Kyoungkook Kang , Gyujin Sim , Geonung Kim , Donguk Kim , Seungho Nam , Sunghyun Cho

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

In this paper, we study video synthesis with emphasis on simplifying the generation conditions. Most existing video synthesis models or datasets are designed to address complex motions of a single object, lacking the ability of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Yang Wu , Zhibin Liu , Hefeng Wu , Liang Lin

We propose an automatic video inpainting algorithm which relies on the optimisation of a global, patch-based functional. Our algorithm is able to deal with a variety of challenging situations which naturally arise in video inpainting, such…

Computer Vision and Pattern Recognition · Computer Science 2017-12-08 Alasdair Newson , Andrés Almansa , Matthieu Fradet , Yann Gousseau , Patrick Pérez

Data augmentation is crucial for improving the robustness of face detection systems, especially under challenging conditions such as occlusion, illumination variation, and complex environments. Traditional copy paste augmentation often…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Qiushi Guo

Diffusion models have enabled high-quality, conditional image editing capabilities. We propose to expand their arsenal, and demonstrate that off-the-shelf diffusion models can be used for a wide range of cross-domain compositing tasks.…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Roy Hachnochi , Mingrui Zhao , Nadav Orzech , Rinon Gal , Ali Mahdavi-Amiri , Daniel Cohen-Or , Amit Haim Bermano

We introduce CinemaWorld, a generative augmented reality system that augments the viewer's physical surroundings with automatically generated mixed reality 3D content extracted from and synchronized with 2D movie scenes. Our system…

Human-Computer Interaction · Computer Science 2026-03-10 Keiichi Ihara , DaeHo Lee , Manato Abe , Hye-Young Jo , Ryo Suzuki

Image generation today can produce somewhat realistic images from text prompts. However, if one asks the generator to synthesize a specific camera setting such as creating different fields of view using a 24mm lens versus a 70mm lens, the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Yu Yuan , Xijun Wang , Yichen Sheng , Prateek Chennuri , Xingguang Zhang , Stanley Chan

Generative image composition aims to regenerate the given foreground object in the background image to produce a realistic composite image. Some high-authenticity methods can adjust foreground pose/view to be compatible with background,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Jingyuan Wang , Li Niu

Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-14 Yingqing He , Menghan Xia , Haoxin Chen , Xiaodong Cun , Yuan Gong , Jinbo Xing , Yong Zhang , Xintao Wang , Chao Weng , Ying Shan , Qifeng Chen

Foundational world models must be both interactive and preserve spatiotemporal coherence for effective future planning with action choices. However, present models for long video generation have limited inherent world modeling capabilities…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Taiye Chen , Xun Hu , Zihan Ding , Chi Jin

Image composition targets at synthesizing a realistic composite image from a pair of foreground and background images. Recently, generative composition methods are built on large pretrained diffusion models to generate composite images,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Bo Zhang , Yuxuan Duan , Jun Lan , Yan Hong , Huijia Zhu , Weiqiang Wang , Li Niu

Realistic shadow generation is crucial for achieving seamless image compositing, yet existing methods primarily focus on single-object insertion and often fail to generalize when multiple foreground objects are composited into a background…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Waqas Ahmed , Dean Diepeveen , Ferdous Sohel

Generative methods for image and video editing use generative models as priors to perform edits despite incomplete information, such as changing the composition of 3D objects shown in a single image. Recent methods have shown promising…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Juil Koo , Paul Guerrero , Chun-Hao Paul Huang , Duygu Ceylan , Minhyuk Sung

As generative models expand the possibilities of visual content creation, layered image synthesis has emerged as a promising direction for controllable and creative editing. However, existing methods struggle to fully realize this…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Kyoungkook Kang , Gyujin Sim , Sunghyun Cho

We propose "factor matting", an alternative formulation of the video matting problem in terms of counterfactual video synthesis that is better suited for re-composition tasks. The goal of factor matting is to separate the contents of video…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Zeqi Gu , Wenqi Xian , Noah Snavely , Abe Davis

We introduce layered controllable video generation, where we, without any supervision, decompose the initial frame of a video into foreground and background layers, with which the user can control the video generation process by simply…

Computer Vision and Pattern Recognition · Computer Science 2022-10-05 Jiahui Huang , Yuhe Jin , Kwang Moo Yi , Leonid Sigal

The visual world we sense, interpret and interact everyday is a complex composition of interleaved physical entities. Therefore, it is a very challenging task to generate vivid scenes of similar complexity using computers. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2019-02-05 Mehmet Ozgur Turkoglu , William Thong , Luuk Spreeuwers , Berkay Kicanaoglu