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Animating a still image offers an engaging visual experience. Traditional image animation techniques mainly focus on animating natural scenes with stochastic dynamics (e.g. clouds and fluid) or domain-specific motions (e.g. human hair or…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Jinbo Xing , Menghan Xia , Yong Zhang , Haoxin Chen , Wangbo Yu , Hanyuan Liu , Xintao Wang , Tien-Tsin Wong , Ying Shan

Recent advancements in character video synthesis still depend on extensive fine-tuning or complex 3D modeling processes, which can restrict accessibility and hinder real-time applicability. To address these challenges, we propose a simple…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Di Qiu , Zheng Chen , Rui Wang , Mingyuan Fan , Changqian Yu , Junshi Huang , Xiang Wen

We propose PostCam, a framework for novel-view video generation that enables post-capture editing of camera trajectories in dynamic scenes. We find that existing video recapture methods suffer from suboptimal camera motion injection…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Yipeng Chen , Zhichao Ye , Zhenzhou Fang , Xinyu Chen , Xiaoyu Zhang , Jialing Liu , Nan Wang , Haomin Liu , Guofeng Zhang

Generating human motion guided by conditions such as textual descriptions is challenging due to the need for datasets with pairs of high-quality motion and their corresponding conditions. The difficulty increases when aiming for finer…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Pablo Ruiz-Ponce , German Barquero , Cristina Palmero , Sergio Escalera , José García-Rodríguez

Current motion-controlled image-to-video generation models rigidly follow user-provided trajectories that are often sparse, imprecise, and causally incomplete. Such reliance often yields unnatural or implausible outcomes, especially by…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Lee Hsin-Ying , Hanwen Jiang , Yiqun Mei , Jing Shi , Ming-Hsuan Yang , Zhixin Shu

Despite significant advancements in customizing text-to-image and video generation models, generating images and videos that effectively integrate multiple personalized concepts remains a challenging task. To address this, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Gihyun Kwon , Jong Chul Ye

Video generation and editing conditioned on text prompts or images have undergone significant advancements. However, challenges remain in accurately controlling global layout and geometry details solely by texts, and supporting motion…

Graphics · Computer Science 2025-04-01 Feng-Lin Liu , Hongbo Fu , Xintao Wang , Weicai Ye , Pengfei Wan , Di Zhang , Lin Gao

Modern video generators still struggle with complex physical dynamics, often falling short of physical realism. Existing approaches address this using external verifiers or additional training on augmented data, which is computationally…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Sangwon Jang , Taekyung Ki , Jaehyeong Jo , Saining Xie , Jaehong Yoon , Sung Ju Hwang

Text-to-video (T2V) diffusion models have shown promising capabilities in synthesizing realistic videos from input text prompts. However, the input text description alone provides limited control over the precise objects movements and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Yen-Siang Wu , Chi-Pin Huang , Fu-En Yang , Yu-Chiang Frank Wang

Textual image generation spans diverse fields like advertising, education, product packaging, social media, information visualization, and branding. Despite recent strides in language-guided image synthesis using diffusion models, current…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Shubham Paliwal , Arushi Jain , Monika Sharma , Vikram Jamwal , Lovekesh Vig

Creating content with specified identities (ID) has attracted significant interest in the field of generative models. In the field of text-to-image generation (T2I), subject-driven creation has achieved great progress with the identity…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Ze Ma , Daquan Zhou , Chun-Hsiao Yeh , Xue-She Wang , Xiuyu Li , Huanrui Yang , Zhen Dong , Kurt Keutzer , Jiashi Feng

Visual effects (VFX) are essential for enhancing the expressiveness and creativity of video content, yet producing high-quality effects typically requires expert knowledge and costly production pipelines. Existing AIGC systems face…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Shiyuan Yang , Ruihuang Li , Jiale Tao , Shuai Shao , Qinglin Lu , Jing Liao

Recent text-to-image generation models have demonstrated impressive capability of generating text-aligned images with high fidelity. However, generating images of novel concept provided by the user input image is still a challenging task.…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Yufan Zhou , Ruiyi Zhang , Tong Sun , Jinhui Xu

Motions in a video primarily consist of camera motion, induced by camera movement, and object motion, resulting from object movement. Accurate control of both camera and object motion is essential for video generation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhouxia Wang , Ziyang Yuan , Xintao Wang , Tianshui Chen , Menghan Xia , Ping Luo , Ying Shan

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

In the realm of image generation, creating customized images from visual prompt with additional textual instruction emerges as a promising endeavor. However, existing methods, both tuning-based and tuning-free, struggle with interpreting…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Jing He , Haodong Li , Yongzhe Hu , Guibao Shen , Yingjie Cai , Weichao Qiu , Ying-Cong Chen

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Hanxin Zhu , Tianyu He , Anni Tang , Junliang Guo , Zhibo Chen , Jiang Bian

The emergence of diffusion models has greatly propelled the progress in image and video generation. Recently, some efforts have been made in controllable video generation, including text-to-video generation and video motion control, among…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Teng Hu , Jiangning Zhang , Ran Yi , Yating Wang , Hongrui Huang , Jieyu Weng , Yabiao Wang , Lizhuang Ma

Creating flexible 3D scenes from a single image is vital when direct 3D data acquisition is costly or impractical. We introduce NavCrafter, a novel framework that explores 3D scenes from a single image by synthesizing novel-view video…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Hongbo Duan , Peiyu Zhuang , Yi Liu , Zhengyang Zhang , Yuxin Zhang , Pengting Luo , Fangming Liu , Xueqian Wang

Recently, breakthroughs in video modeling have allowed for controllable camera trajectories in generated videos. However, these methods cannot be directly applied to user-provided videos that are not generated by a video model. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 David Junhao Zhang , Roni Paiss , Shiran Zada , Nikhil Karnad , David E. Jacobs , Yael Pritch , Inbar Mosseri , Mike Zheng Shou , Neal Wadhwa , Nataniel Ruiz