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Controllable video editing has demonstrated remarkable potential across diverse applications, particularly in scenarios where capturing or re-capturing real-world videos is either impractical or costly. This paper introduces a novel and…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Ziling Liu , Jinyu Yang , Mingqi Gao , Feng Zheng

Recent advances in diffusion-based video generation have opened new possibilities for controllable video editing, yet realistic video object insertion (VOI) remains challenging due to limited 4D scene understanding and inadequate handling…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Hoiyeong Jin , Hyojin Jang , Jeongho Kim , Junha Hyung , Kinam Kim , Dongjin Kim , Huijin Choi , Hyeonji Kim , Jaegul Choo

In this paper, we introduce a new problem of manipulating a given video by inserting other videos into it. Our main task is, given an object video and a scene video, to insert the object video at a user-specified location in the scene video…

Computer Vision and Pattern Recognition · Computer Science 2019-03-18 Donghoon Lee , Tomas Pfister , Ming-Hsuan Yang

This work presents Insert Anything, a unified framework for reference-based image insertion that seamlessly integrates objects from reference images into target scenes under flexible, user-specified control guidance. Instead of training…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Wensong Song , Hong Jiang , Zongxing Yang , Ruijie Quan , Yi Yang

Video editing increasingly demands the ability to incorporate specific real-world instances into existing footage, yet current approaches fundamentally fail to capture the unique visual characteristics of particular subjects and ensure…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Shaobin Zhuang , Zhipeng Huang , Binxin Yang , Ying Zhang , Fangyikang Wang , Canmiao Fu , Chong Sun , Zheng-Jun Zha , Chen Li , Yali Wang

Recent developments in generative diffusion models have turned many dreams into realities. For video object insertion, existing methods typically require additional information, such as a reference video or a 3D asset of the object, to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Qi Zhao , Zhan Ma , Pan Zhou

We propose a method to realistically insert synthetic objects into existing photographs without requiring access to the scene or any additional scene measurements. With a single image and a small amount of annotation, our method creates a…

Graphics · Computer Science 2019-12-30 Kevin Karsch , Varsha Hedau , David Forsyth , Derek Hoiem

The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formation process. While recent large-scale diffusion models have…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Ruofan Liang , Zan Gojcic , Merlin Nimier-David , David Acuna , Nandita Vijaykumar , Sanja Fidler , Zian Wang

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 present Material Anything, a fully-automated, unified diffusion framework designed to generate physically-based materials for 3D objects. Unlike existing methods that rely on complex pipelines or case-specific optimizations, Material…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Xin Huang , Tengfei Wang , Ziwei Liu , Qing Wang

Monocular depth estimation is crucial for tracking and reconstruction algorithms, particularly in the context of surgical videos. However, the inherent challenges in directly obtaining ground truth depth maps during surgery render…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Ange Lou , Yamin Li , Yike Zhang , Jack Noble

The insertion of objects into a scene and relighting are commonly utilized applications in augmented reality (AR). Previous methods focused on inserting virtual objects using CAD models or real objects from single-view images, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Xuening Zhu , Renjiao Yi , Xin Wen , Chenyang Zhu , Kai Xu

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

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

Despite significant advancements in video generation, inserting a given object into videos remains a challenging task. The difficulty lies in preserving the appearance details of the reference object and accurately modeling coherent motions…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Yuanpeng Tu , Hao Luo , Xi Chen , Sihui Ji , Xiang Bai , Hengshuang Zhao

In this paper, we propose a novel network framework for indoor 3D object detection to handle variable input frame numbers in practical scenarios. Existing methods only consider fixed frames of input data for a single detector, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Zhenyu Wu , Xiuwei Xu , Ziwei Wang , Chong Xia , Linqing Zhao , Jiwen Lu , Haibin Yan

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

Creating high-quality and interactive virtual environments, such as games and simulators, often involves complex and costly manual modeling processes. In this paper, we present Video2Game, a novel approach that automatically converts videos…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Hongchi Xia , Zhi-Hao Lin , Wei-Chiu Ma , Shenlong Wang

3D reconstruction from a single-RGB image in unconstrained real-world scenarios presents numerous challenges due to the inherent diversity and complexity of objects and environments. In this paper, we introduce Anything-3D, a methodical…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Qiuhong Shen , Xingyi Yang , Xinchao Wang

Recent advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has made impressive progress in addressing the challenges of…

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