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Camera and object motions are central to a video's narrative. However, precisely editing these captured motions remains a significant challenge, especially under complex object movements. Current motion-controlled image-to-video (I2V)…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Yao-Chih Lee , Zhoutong Zhang , Jiahui Huang , Jui-Hsien Wang , Joon-Young Lee , Jia-Bin Huang , Eli Shechtman , Zhengqi Li

There has been significant progresses for image object detection in recent years. Nevertheless, video object detection has received little attention, although it is more challenging and more important in practical scenarios. Built upon the…

Computer Vision and Pattern Recognition · Computer Science 2017-12-01 Xizhou Zhu , Jifeng Dai , Lu Yuan , Yichen Wei

Methods for image-to-video generation have achieved impressive, photo-realistic quality. However, adjusting specific elements in generated videos, such as object motion or camera movement, is often a tedious process of trial and error,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-26 Koichi Namekata , Sherwin Bahmani , Ziyi Wu , Yash Kant , Igor Gilitschenski , David B. Lindell

Camera redirection aims to replay a dynamic scene from a single monocular video under a user-specified camera trajectory. However, large-angle redirection is inherently ill-posed: a monocular video captures only a narrow spatio-temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Wei Cao , Hao Zhang , Fengrui Tian , Yulun Wu , Yingying Li , Shenlong Wang , Ning Yu , Yaoyao Liu

This paper introduces Point2Insert, a sparse-point-based framework for flexible and user-friendly object insertion in videos, motivated by the growing popularity of accurate, low-effort object placement. Existing approaches face two major…

Computer Vision and Pattern Recognition · Computer Science 2026-02-05 Yu Zhou , Xiaoyan Yang , Bojia Zi , Lihan Zhang , Ruijie Sun , Weishi Zheng , Haibin Huang , Chi Zhang , Xuelong Li

Today, people can easily record memorable moments, ranging from concerts, sports events, lectures, family gatherings, and birthday parties with multiple consumer cameras. However, synchronizing these cross-camera streams remains…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Shaowei Liu , David Yifan Yao , Saurabh Gupta , Shenlong Wang

Inpainting algorithms have achieved remarkable progress in removing objects from images, yet still face two challenges: 1) struggle to handle the object's visual effects such as shadow and reflection; 2) easily generate shape-like artifacts…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Runpu Wei , Zijin Yin , Shuo Zhang , Lanxiang Zhou , Xueyi Wang , Chao Ban , Tianwei Cao , Hao Sun , Zhongjiang He , Kongming Liang , Zhanyu Ma

In this paper, we present a novel robust framework for low-level vision tasks, including denoising, object removal, frame interpolation, and super-resolution, that does not require any external training data corpus. Our proposed approach…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Gaurav Shrivastava , Ser-Nam Lim , Abhinav Shrivastava

Self-captured full-body videos are popular, but most deployments require mounted cameras, carefully-framed shots, and repeated practice. We propose a more convenient solution that enables full-body video capture using handheld mobile…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Bowei Chen , Brian Curless , Ira Kemelmacher-Shlizerman , Steven M. Seitz

Pose transfer of human videos aims to generate a high fidelity video of a target person imitating actions of a source person. A few studies have made great progress either through image translation with deep latent features or neural…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Yang-tian Sun , Hao-zhi Huang , Xuan Wang , Yu-kun Lai , Wei Liu , Lin Gao

Text-guided image-to-video (I2V) generation aims to generate a coherent video that preserves the identity of the input image and semantically aligns with the input prompt. Existing methods typically augment pretrained text-to-video (T2V)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Xun Guo , Mingwu Zheng , Liang Hou , Yuan Gao , Yufan Deng , Pengfei Wan , Di Zhang , Yufan Liu , Weiming Hu , Zhengjun Zha , Haibin Huang , Chongyang Ma

We propose an attention-based networks for transferring motions between arbitrary objects. Given a source image(s) and a driving video, our networks animate the subject in the source images according to the motion in the driving video. In…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Subin Jeon , Seonghyeon Nam , Seoung Wug Oh , Seon Joo Kim

Video world models aim to simulate dynamic, real-world environments, yet existing methods struggle to provide unified and precise control over camera and multi-object motion, as videos inherently capture dynamics in the projected 2D image…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Sixiao Zheng , Minghao Yin , Wenbo Hu , Xiaoyu Li , Ying Shan , Yanwei Fu

Videos convey richer information than images or text, capturing both spatial and temporal dynamics. However, most existing video customization methods rely on reference images or task-specific temporal priors, failing to fully exploit the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Pengze Zhang , Yanze Wu , Mengtian Li , Xu Bai , Songtao Zhao , Fulong Ye , Chong Mou , Xinghui Li , Zhuowei Chen , Qian He , Mingyuan Gao

Video (camera) trajectory editing aims to synthesize new videos that follow user-defined camera paths while preserving scene content and plausibly inpainting previously unseen regions, upgrading amateur footage into professionally styled…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Zhihao Shi , Kejia Yin , Weilin Wan , Yuhongze Zhou , Yuanhao Yu , Xinxin Zuo , Qiang Sun , Juwei Lu

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

This paper improves upon the Pix2Seq object detector by extending it for videos. In the process, it introduces a new way to perform end-to-end video object detection that improves upon existing video detectors in two key ways. First, by…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Abhineet Singh , Nilanjan Ray

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

The "one-shot" technique represents a distinct and sophisticated aesthetic in filmmaking. However, its practical realization is often hindered by prohibitive costs and complex real-world constraints. Although emerging video generation…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jiawei Liu , Junqiao Li , Jiangfan Deng , Gen Li , Siyu Zhou , Zetao Fang , Shanshan Lao , Zengde Deng , Jianing Zhu , Tingting Ma , Jiayi Li , Yunqiu Wang , Qian He , Xinglong Wu

We introduce MapAnything, a unified transformer-based feed-forward model that ingests one or more images along with optional geometric inputs such as camera intrinsics, poses, depth, or partial reconstructions, and then directly regresses…