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Cinemagraphs are short looping videos created by adding subtle motions to a static image. This kind of media is popular and engaging. However, automatic generation of cinemagraphs is an underexplored area and current solutions require…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Hugo Bertiche , Niloy J. Mitra , Kuldeep Kulkarni , Chun-Hao Paul Huang , Tuanfeng Y. Wang , Meysam Madadi , Sergio Escalera , Duygu Ceylan

Cinematic storytelling is profoundly shaped by the artful manipulation of photographic elements such as depth of field and exposure. These effects are crucial in conveying mood and creating aesthetic appeal. However, controlling these…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Huiqiang Sun , Liao Shen , Zhan Peng , Kun Wang , Size Wu , Yuhang Zang , Tianqi Liu , Zihao Huang , Xingyu Zeng , Zhiguo Cao , Wei Li , Chen Change Loy

We present an algorithm for producing a seamless animated loop from a single image. The algorithm detects periodic structures, such as the windows of a building or the steps of a staircase, and generates a non-trivial displacement vector…

Computer Vision and Pattern Recognition · Computer Science 2021-05-21 Tavi Halperin , Hanit Hakim , Orestis Vantzos , Gershon Hochman , Netai Benaim , Lior Sassy , Michael Kupchik , Ofir Bibi , Ohad Fried

There is a rapidly growing interest in controlling consistency across multiple generated images using diffusion models. Among various methods, recent works have found that simply manipulating attention modules by concatenating features from…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jiaojiao Fan , Haotian Xue , Qinsheng Zhang , Yongxin Chen

This paper proposes an algorithm that turns a regular video capturing urban scenes into a high-quality endless animation, known as a Cinemagraph. The creation of a Cinemagraph usually requires a static camera in a carefully configured…

Computer Vision and Pattern Recognition · Computer Science 2016-12-06 Hang Yan , Yebin Liu , Yasutaka Furukawa

Controllable video synthesis is a central challenge in computer vision, yet current models struggle with fine grained control beyond textual prompts, particularly for cinematic attributes like camera trajectory and genre. Existing datasets…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Zahra Dehghanian , Morteza Abolghasemi , Hamid Beigy , Hamid R. Rabiee

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

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

Despite recent progress, video diffusion models still struggle to synthesize realistic videos involving highly dynamic motions or requiring fine-grained motion controllability. A central limitation lies in the scarcity of such examples in…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Wonjoon Jin , Jiyun Won , Janghyeok Han , Qi Dai , Chong Luo , Seung-Hwan Baek , Sunghyun Cho

We present a unified controllable video generation approach AnimateAnything that facilitates precise and consistent video manipulation across various conditions, including camera trajectories, text prompts, and user motion annotations.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Guojun Lei , Chi Wang , Hong Li , Rong Zhang , Yikai Wang , Weiwei Xu

Although humans have the innate ability to imagine multiple possible actions from videos, it remains an extraordinary challenge for computers due to the intricate camera movements and montages. Most existing motion generation methods…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Liangdong Qiu , Chengxing Yu , Yanran Li , Zhao Wang , Haibin Huang , Chongyang Ma , Di Zhang , Pengfei Wan , Xiaoguang Han

Specifying nuanced and compelling camera motion remains a significant hurdle for non-expert creators using generative tools, creating an "expressive gap" where generic text prompts fail to capture cinematic vision. This barrier limits…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Pooja Guhan , Divya Kothandaraman , Geonsun Lee , Tsung-Wei Huang , Guan-Ming Su , Dinesh Manocha

Panoramic video generation has attracted growing attention due to its applications in virtual reality and immersive media. However, existing methods lack explicit motion control and struggle to generate scenes with large and complex…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Cheng Zhang , Hanwen Liang , Donny Y. Chen , Qianyi Wu , Konstantinos N. Plataniotis , Camilo Cruz Gambardella , Jianfei Cai

Training a generative model on a single human skeletal motion sequence without being bound to a specific kinematic tree has drawn significant attention from the animation community. Unlike text-to-motion generation, single-shot models allow…

Graphics · Computer Science 2025-08-27 Eleni Tselepi , Spyridon Thermos , Gerasimos Potamianos

Cinemagraphs are a compelling way to convey dynamic aspects of a scene. In these media, dynamic and still elements are juxtaposed to create an artistic and narrative experience. Creating a high-quality, aesthetically pleasing cinemagraph…

Computer Vision and Pattern Recognition · Computer Science 2017-08-11 Tae-Hyun Oh , Kyungdon Joo , Neel Joshi , Baoyuan Wang , In So Kweon , Sing Bing Kang

Recent advancements in text-to-video (T2V) generation have leveraged diffusion models to enhance visual coherence in videos synthesized from textual descriptions. However, existing research primarily focuses on object motion, often…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Xiaozhe Li , Kai WU , Siyi Yang , YiZhan Qu , Guohua. Zhang , Zhiyu Chen , Jiayao Li , Jiangchuan Mu , Xiaobin Hu , Wen Fang , Mingliang Xiong , Hao Deng , Qingwen Liu , Gang Li , Bin He

Realistic shadow generation is a critical component for high-quality image compositing and visual effects, yet existing methods suffer from certain limitations: Physics-based approaches require a 3D scene geometry, which is often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Onur Tasar , Clément Chadebec , Benjamin Aubin

Imagining multiple consecutive frames given one single snapshot is challenging, since it is difficult to simultaneously predict diverse motions from a single image and faithfully generate novel frames without visual distortions. In this…

Computer Vision and Pattern Recognition · Computer Science 2019-03-05 Lu Sheng , Junting Pan , Jiaming Guo , Jing Shao , Xiaogang Wang , Chen Change Loy

Camera trajectory design plays a crucial role in video production, serving as a fundamental tool for conveying directorial intent and enhancing visual storytelling. In cinematography, Directors of Photography meticulously craft camera…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Mengchen Zhang , Tong Wu , Jing Tan , Ziwei Liu , Gordon Wetzstein , Dahua Lin

Diffusion models excel at photorealistic synthesis but struggle with precise object counts, especially in high-density settings. We introduce COUNTLOOP, a training-free framework that achieves precise instance control through iterative,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Anindya Mondal , Ayan Banerjee , Sauradip Nag , Josep Llados , Xiatian Zhu , Anjan Dutta
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