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Recent advancements in camera-trajectory-guided image-to-video generation offer higher precision and better support for complex camera control compared to text-based approaches. However, they also introduce significant usability challenges,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Teng Li , Guangcong Zheng , Rui Jiang , Shuigen Zhan , Tao Wu , Yehao Lu , Yining Lin , Chuanyun Deng , Yepan Xiong , Min Chen , Lin Cheng , Xi Li

Camera control has been extensively studied in conditioned video generation; however, performing precisely altering the camera trajectories while faithfully preserving the video content remains a challenging task. The mainstream approach to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Dong-Yu Chen , Yixin Guo , Shuojin Yang , Tai-Jiang Mu , Shi-Min Hu

We present a method for generating video sequences with coherent motion between a pair of input key frames. We adapt a pretrained large-scale image-to-video diffusion model (originally trained to generate videos moving forward in time from…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Xiaojuan Wang , Boyang Zhou , Brian Curless , Ira Kemelmacher-Shlizerman , Aleksander Holynski , Steven M. Seitz

Image-to-video (I2V) generation seeks to produce realistic motion sequences from a single reference image. Although recent methods exhibit strong temporal consistency, they often struggle when dealing with complex, non-repetitive human…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Ashkan Taghipour , Morteza Ghahremani , Mohammed Bennamoun , Farid Boussaid , Aref Miri Rekavandi , Zinuo Li , Qiuhong Ke , Hamid Laga

We introduce Follow-Your-Creation, a novel 4D video creation framework capable of both generating and editing 4D content from a single monocular video input. By leveraging a powerful video inpainting foundation model as a generative prior,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Yue Ma , Kunyu Feng , Xinhua Zhang , Hongyu Liu , David Junhao Zhang , Jinbo Xing , Yinhan Zhang , Ayden Yang , Zeyu Wang , Qifeng Chen

In recent years, diffusion models have been widely adopted for image inpainting tasks due to their powerful generative capabilities, achieving impressive results. Existing multimodal inpainting methods based on diffusion models often…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Qimin Wang , Xinda Liu , Guohua Geng

Video frame interpolation is an important low-level vision task, which can increase frame rate for more fluent visual experience. Existing methods have achieved great success by employing advanced motion models and synthesis networks.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Lingtong Kong , Boyuan Jiang , Donghao Luo , Wenqing Chu , Ying Tai , Chengjie Wang , Jie Yang

Recently, image-to-video (I2V) diffusion models have demonstrated impressive scene understanding and generative quality, incorporating image conditions to guide generation. However, these models primarily animate static images without…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Luis Denninger , Sina Mokhtarzadeh Azar , Juergen Gall

Instructional video editing applies edits to an input video using only text prompts, enabling intuitive natural-language control. Despite rapid progress, most methods still require fixed-length inputs and substantial compute. Meanwhile,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Mohammadreza Salehi , Mehdi Noroozi , Luca Morreale , Ruchika Chavhan , Malcolm Chadwick , Alberto Gil Ramos , Abhinav Mehrotra

Humans can easily imagine a scene from auditory information based on their prior knowledge of audio-visual events. In this paper, we mimic this innate human ability in deep learning models to improve the quality of video inpainting. To…

Audio and Speech Processing · Electrical Eng. & Systems 2023-10-12 Kyuyeon Kim , Junsik Jung , Woo Jae Kim , Sung-Eui Yoon

Recent advances in video generation have been dominated by diffusion and flow-matching models, which produce high-quality results but remain computationally intensive and difficult to scale. In this work, we introduce VideoAR, the first…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Longbin Ji , Xiaoxiong Liu , Junyuan Shang , Shuohuan Wang , Yu Sun , Hua Wu , Haifeng Wang

Contemporary Video Instance Segmentation (VIS) methods typically adhere to a pre-train then fine-tune regime, where a segmentation model trained on images is fine-tuned on videos. However, the lack of temporal knowledge in the pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Qing Zhong , Peng-Tao Jiang , Wen Wang , Guodong Ding , Lin Wu , Kaiqi Huang

Vision Transformers (ViTs) have demonstrated state-ofthe-art performance in several benchmarks, yet their high computational costs hinders their practical deployment. Patch Pruning offers significant savings, but existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Patrick Glandorf , Thomas Norrenbrock , Bodo Rosenhahn

Text-driven 3D editing enables user-friendly 3D object or scene editing with text instructions. Due to the lack of multi-view consistency priors, existing methods typically resort to employing 2D generation or editing models to process each…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Liyi Chen , Ruihuang Li , Guowen Zhang , Pengfei Wang , Lei Zhang

This paper proposes a novel video inpainting method. We make three main contributions: First, we extended previous Transformers with patch alignment by introducing Deformed Patch-based Homography (DePtH), which improves patch-level feature…

Computer Vision and Pattern Recognition · Computer Science 2022-09-29 Jiayin Cai , Changlin Li , Xin Tao , Chun Yuan , Yu-Wing Tai

Existing models often struggle with complex temporal changes, particularly when generating videos with gradual attribute transitions. The most common prompt interpolation approach for motion transitions often fails to handle gradual…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Ling Lo , Kelvin C. K. Chan , Wen-Huang Cheng , Ming-Hsuan Yang

Video object insertion is a critical task for dynamically inserting new objects into existing environments. Previous video generation methods focus primarily on synthesizing entire scenes while struggling with ensuring consistent object…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Xia Qi , Peishan Cong , Yichen Yao , Ziyi Wang , Yaoqin Ye , Yuexin Ma

Video frame interpolation (VFI) is the task that synthesizes the intermediate frame given two consecutive frames. Most of the previous studies have focused on appropriate frame warping operations and refinement modules for the warped…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Sangjin Lee , Hyeongmin Lee , Chajin Shin , Hanbin Son , Sangyoun Lee

Video object removal and inpainting are critical tasks in the fields of computer vision and multimedia processing, aimed at restoring missing or corrupted regions in video sequences. Traditional methods predominantly rely on flow-based…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Jie Liu , Zheng Hui

Video stabilization is a fundamental and important technique for higher quality videos. Prior works have extensively explored video stabilization, but most of them involve cropping of the frame boundaries and introduce moderate levels of…

Computer Vision and Pattern Recognition · Computer Science 2019-09-09 Jinsoo Choi , In So Kweon
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