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We present Fillerbuster, a unified model that completes unknown regions of a 3D scene with a multi-view latent diffusion transformer. Casual captures are often sparse and miss surrounding content behind objects or above the scene. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Ethan Weber , Norman Müller , Yash Kant , Vasu Agrawal , Michael Zollhöfer , Angjoo Kanazawa , Christian Richardt

Recent image generation models produce impressive composites, but often fail to preserve the identity of user-provided content when editing specific elements: the surrounding scene may shift, and even the edited object's appearance can…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Jinrui Yang , Qing Liu , Yijun Li , Mengwei Ren , Letian Zhang , Zhe Lin , Cihang Xie , Yuyin Zhou

Many compelling video processing effects can be achieved if per-pixel depth information and 3D camera calibrations are known. However, the success of such methods is highly dependent on the accuracy of this "scene-space" information. We…

Computer Vision and Pattern Recognition · Computer Science 2021-02-08 Felix Klose , Oliver Wang , Jean-Charles Bazin , Marcus Magnor , Alexander Sorkine-Hornung

Over-the-shoulder dialogue videos are essential in films, short dramas, and advertisements, providing visual variety and enhancing viewers' emotional connection. Despite their importance, such dialogue scenes remain largely underexplored in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Yuang Zhang , Junqi Cheng , Haoyu Zhao , Jiaxi Gu , Fangyuan Zou , Zenghui Lu , Peng Shu

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Junjie Cao , Kaizhou Li , Xinchun Yu , Hongxiang Li , Xiaoping Zhang

Image fusion is famous as an alternative solution to generate one high-quality image from multiple images in addition to image restoration from a single degraded image. The essence of image fusion is to integrate complementary information…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Pengwei Liang , Junjun Jiang , Qing Ma , Xianming Liu , Jiayi Ma

Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content. However, the scarcity of 3D scene datasets constrains current methodologies to primarily object-centric…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Dejia Xu , Hanwen Liang , Neel P. Bhatt , Hezhen Hu , Hanxue Liang , Konstantinos N. Plataniotis , Zhangyang Wang

Generating interaction-centric videos, such as those depicting humans or robots interacting with objects, is crucial for embodied intelligence, as they provide rich and diverse visual priors for robot learning, manipulation policy training,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Gen Li , Bo Zhao , Jianfei Yang , Laura Sevilla-Lara

State-of-the-art video action classifiers often suffer from overfitting. They tend to be biased towards specific objects and scene cues, rather than the foreground action content, leading to sub-optimal generalization performances. Recent…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Sangdoo Yun , Seong Joon Oh , Byeongho Heo , Dongyoon Han , Jinhyung Kim

Object compositing offers significant promise for augmented reality (AR) and embodied intelligence applications. Existing approaches predominantly focus on single-image scenarios or intrinsic decomposition techniques, facing challenges with…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Kerui Ren , Jiayang Bai , Linning Xu , Lihan Jiang , Jiangmiao Pang , Mulin Yu , Bo Dai

We present a framework for document-centric background generation with multi-page editing and thematic continuity. To ensure text regions remain readable, we employ a \emph{latent masking} formulation that softly attenuates updates in the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Taewon Kang , Joseph K J , Chris Tensmeyer , Jihyung Kil , Wanrong Zhu , Ming C. Lin , Vlad I. Morariu

Generating realistic and controllable weather effects in videos is valuable for many applications. Physics-based weather simulation requires precise reconstructions that are hard to scale to in-the-wild videos, while current video editing…

Graphics · Computer Science 2025-07-22 Chih-Hao Lin , Zian Wang , Ruofan Liang , Yuxuan Zhang , Sanja Fidler , Shenlong Wang , Zan Gojcic

Large-scale video generative models can synthesize diverse and realistic visual content for dynamic world creation, but they often lack element-wise controllability, hindering their use in editing scenes and training embodied AI agents. We…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Sicheng Mo , Ziyang Leng , Leon Liu , Weizhen Wang , Honglin He , Bolei Zhou

In this work, we present a method for turning Chinese still-life paintings with global illumination effects into dynamic paintings with moving lights. Our goal is to preserve the original look and feel of still-life paintings with moving…

Graphics · Computer Science 2023-12-12 Sitong Deng , Ergun Akleman

Existing DeepFake detection techniques primarily focus on facial manipulations, such as face-swapping or lip-syncing. However, advancements in text-to-video (T2V) and image-to-video (I2V) generative models now allow fully AI-generated…

Computer Vision and Pattern Recognition · Computer Science 2025-09-04 Rohit Kundu , Hao Xiong , Vishal Mohanty , Athula Balachandran , Amit K. Roy-Chowdhury

Video composition aims to generate a composite video by combining the foreground of one video with the background of another video, but the inserted foreground may be incompatible with the background in terms of color and illumination.…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Xinyuan Lu , Shengyuan Huang , Li Niu , Wenyan Cong , Liqing Zhang

We present VEnhancer, a generative space-time enhancement framework that improves the existing text-to-video results by adding more details in spatial domain and synthetic detailed motion in temporal domain. Given a generated low-quality…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Jingwen He , Tianfan Xue , Dongyang Liu , Xinqi Lin , Peng Gao , Dahua Lin , Yu Qiao , Wanli Ouyang , Ziwei Liu

Collaborative driving systems leverage vehicle-to-everything (V2X) communication for multi-agent collaborative perception to enhance driving safety, yet they remain constrained by scarce annotated real-world V2X driving datasets and limited…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Yihang Tao , Yu Guo , Senkang Hu , Yanan Ma , Zihan Fang , Sam Kwong , Yuguang Fang

Generating high-quality textures for 3D assets is a challenging task. Existing multiview texture generation methods suffer from the multiview inconsistency and missing textures on unseen parts, while UV inpainting texture methods do not…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zheng Zhang , Qinchuan Zhang , Yuteng Ye , Zhi Chen , Penglei Ji , Mengfei Li , Wenxiao Zhang , Yuan Liu

Decomposing a video into a layer-based representation is crucial for easy video editing for the creative industries, as it enables independent editing of specific layers. Existing video-layer decomposition models rely on implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Maria Pilligua , Danna Xue , Javier Vazquez-Corral