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Image-to-Video (I2V) generation synthesizes dynamic visual content from image and text inputs, providing significant creative control. However, the security of such multimodal systems, particularly their vulnerability to jailbreak attacks,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Songping Wang , Rufan Qian , Yueming Lyu , Qinglong Liu , Linzhuang Zou , Jie Qin , Songhua Liu , Caifeng Shan

We propose a zero-shot approach for generating consistent videos of animated characters based on Text-to-Image (T2I) diffusion models. Existing Text-to-Video (T2V) methods are expensive to train and require large-scale video datasets to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Abdelrahman Eldesokey , Peter Wonka

Image reconstruction and image synthesis are important for handling incomplete multimodal imaging data, but existing methods require various task-specific models, complicating training and deployment workflows. We introduce Any2all, a…

Image and Video Processing · Electrical Eng. & Systems 2026-02-10 Weijie Gan , Xucheng Wang , Tongyao Wang , Wenshang Wang , Chunwei Ying , Yuyang Hu , Yasheng Chen , Hongyu An , Ulugbek S. Kamilov

Recent text-to-video (T2V) generation methods have seen significant advancements. However, the majority of these works focus on producing short video clips of a single event (i.e., single-scene videos). Meanwhile, recent large language…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Han Lin , Abhay Zala , Jaemin Cho , Mohit Bansal

Text-to-video generation has advanced rapidly, but existing methods typically output only the final composited video and lack editable layered representations, limiting their use in professional workflows. We propose \textbf{LayerT2V}, a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Guangzhao Li , Kangrui Cen , Baixuan Zhao , Yi Xin , Siqi Luo , Guangtao Zhai , Lei Zhang , Xiaohong Liu

Text-to-image (T2I) diffusion models have shown remarkable success in generating high-quality images from text prompts. Recent efforts extend these models to incorporate conditional images (e.g., canny edge) for fine-grained spatial…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Liheng Zhang , Lexi Pang , Hang Ye , Xiaoxuan Ma , Yizhou Wang

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video…

Computer Vision and Pattern Recognition · Computer Science 2021-06-29 Doyeon Kim , Donggyu Joo , Junmo Kim

Within recent approaches to text-to-video (T2V) generation, achieving controllability in the synthesized video is often a challenge. Typically, this issue is addressed by providing low-level per-frame guidance in the form of edge maps,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Wan-Duo Kurt Ma , J. P. Lewis , W. Bastiaan Kleijn

Chinese landscape painting is a gem of Chinese cultural and artistic heritage that showcases the splendor of nature through the deep observations and imaginations of its painters. Limited by traditional techniques, these artworks were…

Multimedia · Computer Science 2024-04-22 Dingming Liu , Shaowei Li , Ruoyan Zhou , Lili Liang , Yongguan Hong , Fei Chao , Rongrong Ji

Benefiting from large-scale pre-training of text-video pairs, current text-to-video (T2V) diffusion models can generate high-quality videos from the text description. Besides, given some reference images or videos, the parameter-efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Xiuli Bi , Jian Lu , Bo Liu , Xiaodong Cun , Yong Zhang , Weisheng Li , Bin Xiao

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

Video Diffusion Models (VDMs) offer a promising approach for simulating dynamic scenes and environments, with broad applications in robotics and media generation. However, existing models often generate temporally incoherent content that…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zhexiao Xiong , Yizhi Song , Liu He , Wei Xiong , Yu Yuan , Feng Qiao , Nathan Jacobs

Existing DeepFake detection techniques primarily focus on facial manipulations, such as face-swapping or lip-syncing. However, advancements in text-to-video (T2V) and image-to-video (I2V) generative models now allow fully AI-generated…

Computer Vision and Pattern Recognition · Computer Science 2025-09-04 Rohit Kundu , Hao Xiong , Vishal Mohanty , Athula Balachandran , Amit K. Roy-Chowdhury

The generation of humanoid animation from text prompts can profoundly impact animation production and AR/VR experiences. However, existing methods only generate body motion data, excluding facial expressions and hand movements. This…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Mingdian Liu , Yilin Liu , Gurunandan Krishnan , Karl S Bayer , Bing Zhou

Video-to-Video synthesis (Vid2Vid) has achieved remarkable results in generating a photo-realistic video from a sequence of semantic maps. However, this pipeline suffers from high computational cost and long inference latency, which largely…

Computer Vision and Pattern Recognition · Computer Science 2022-07-12 Long Zhuo , Guangcong Wang , Shikai Li , Wayne Wu , Ziwei Liu

Large foundation models have recently emerged as a prominent focus of interest, attaining superior performance in widespread scenarios. Due to the scarcity of 3D data, many efforts have been made to adapt pre-trained transformers from…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Yiwen Tang , Ray Zhang , Jiaming Liu , Zoey Guo , Dong Wang , Zhigang Wang , Bin Zhao , Shanghang Zhang , Peng Gao , Hongsheng Li , Xuelong Li

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image editing research aims to empower users to manipulate generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Chuanming Tang , Kai Wang , Fei Yang , Joost van de Weijer

Event-based cameras offer unique advantages such as high temporal resolution, high dynamic range, and low power consumption. However, the massive storage requirements and I/O burdens of existing synthetic data generation pipelines and the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Hanyue Lou , Jinxiu Liang , Minggui Teng , Yi Wang , Boxin Shi

Trajectory-Guided image-to-video (I2V) generation aims to synthesize videos that adhere to user-specified motion instructions. Existing methods typically rely on computationally expensive fine-tuning on scarce annotated datasets. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Ruicheng Zhang , Jun Zhou , Zunnan Xu , Zihao Liu , Jiehui Huang , Mingyang Zhang , Yu Sun , Xiu Li
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