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Related papers: T2VSafetyBench: Evaluating the Safety of Text-to-V…

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Thanks to recent advancements in scalable deep architectures and large-scale pretraining, text-to-video generation has achieved unprecedented capabilities in producing high-fidelity, instruction-following content across a wide range of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Xuyang Guo , Jiayan Huo , Zhenmei Shi , Zhao Song , Jiahao Zhang , Jiale Zhao

Text-to-video (T2V) generative models have advanced significantly, yet their ability to compose different objects, attributes, actions, and motions into a video remains unexplored. Previous text-to-video benchmarks also neglect this…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Kaiyue Sun , Kaiyi Huang , Xian Liu , Yue Wu , Zihan Xu , Zhenguo Li , Xihui Liu

Text-to-video (T2V) models have shown remarkable performance in generating visually reasonable scenes, while their capability to leverage world knowledge for ensuring semantic consistency and factual accuracy remains largely understudied.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Yubin Chen , Xuyang Guo , Zhenmei Shi , Zhao Song , Jiahao Zhang

Text-to-Video (T2V) models have demonstrated remarkable capability in generating temporally coherent videos from natural language prompts, yet they also risk producing unsafe content such as violence or explicit material. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Quanchen Zou , Nizhang Li , Wenxin Zhang , Jiaye Lin , Yangchen Zeng , Xiangzheng Zhang , Zonghao Ying

Recently, open-domain text-to-video (T2V) generation models have made remarkable progress. However, the promising results are mainly shown by the qualitative cases of generated videos, while the quantitative evaluation of T2V models still…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yuanxin Liu , Lei Li , Shuhuai Ren , Rundong Gao , Shicheng Li , Sishuo Chen , Xu Sun , Lu Hou

Recent advances in text-to-video (T2V) technology, as demonstrated by models such as Runway Gen-3, Pika, Sora, and Kling, have significantly broadened the applicability and popularity of the technology. This progress has created a growing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Zelu Qi , Ping Shi , Shuqi Wang , Chaoyang Zhang , Fei Zhao , Zefeng Ying , Da Pan , Xi Yang , Zheqi He , Teng Dai

Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains. However, these models present notable safety concerns, including the risk of generating harmful,…

Computation and Language · Computer Science 2025-07-28 Lijun Li , Zhelun Shi , Xuhao Hu , Bowen Dong , Yiran Qin , Xihui Liu , Lu Sheng , Jing Shao

Generative models have driven significant progress in a variety of AI tasks, including text-to-video generation, where models like Video LDM and Stable Video Diffusion can produce realistic, movie-level videos from textual instructions.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xuyang Guo , Zekai Huang , Jiayan Huo , Yingyu Liang , Zhenmei Shi , Zhao Song , Jiahao Zhang

Text-to-video (T2V) generation models have made significant progress in creating visually appealing videos. However, they struggle with generating coherent sequential narratives that require logical progression through multiple events.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Zhengxu Tang , Zizheng Wang , Luning Wang , Zitao Shuai , Chenhao Zhang , Siyu Qian , Yirui Wu , Bohao Wang , Haosong Rao , Zhenyu Yang , Chenwei Wu

Recent progress in video generative models has enabled the creation of high-quality videos from multimodal prompts that combine text and images. While these systems offer enhanced controllability, they also introduce new safety risks, as…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Ruize Ma , Minghong Cai , Yilei Jiang , Jiaming Han , Yi Feng , Yingshui Tan , Xiaoyong Zhu , Bo Zhang , Bo Zheng , Xiangyu Yue

Text-to-video generative models have made significant strides in recent years, producing high-quality videos that excel in both aesthetic appeal and accurate instruction following, and have become central to digital art creation and user…

Machine Learning · Computer Science 2025-05-02 Xuyang Guo , Jiayan Huo , Zhenmei Shi , Zhao Song , Jiahao Zhang , Jiale Zhao

The recent rapid advancement of Text-to-Video (T2V) generation technologies are engaging the trained models with more world model ability, making the existing benchmarks increasingly insufficient to evaluate state-of-the-art T2V models.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Zeqing Wang , Xinyu Wei , Bairui Li , Zhen Guo , Jinrui Zhang , Hongyang Wei , Keze Wang , Lei Zhang

Recent advances in text-to-video generation have achieved impressive performance on short clips, yet evaluating long-form generation under complex textual inputs remains a significant challenge. In response to this challenge, we present…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xiangqing Zheng , Chengyue Wu , Kehai Chen , Min Zhang

In recent years, fueled by the rapid advancement of diffusion models, text-to-video (T2V) generation models have achieved remarkable progress, with notable examples including Pika, Luma, Kling, and Open-Sora. Although these models exhibit…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Jiayang Liu , Siyuan Liang , Shiqian Zhao , Rongcheng Tu , Wenbo Zhou , Aishan Liu , Dacheng Tao , Siew Kei Lam

Text-to-video (T2V) models like Sora have made significant strides in visualizing complex prompts, which is increasingly viewed as a promising path towards constructing the universal world simulator. Cognitive psychologists believe that the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Fanqing Meng , Jiaqi Liao , Xinyu Tan , Wenqi Shao , Quanfeng Lu , Kaipeng Zhang , Yu Cheng , Dianqi Li , Yu Qiao , Ping Luo

High-quality video generation, encompassing text-to-video (T2V), image-to-video (I2V), and video-to-video (V2V) generation, holds considerable significance in content creation to benefit anyone express their inherent creativity in new ways…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Ailing Zeng , Yuhang Yang , Weidong Chen , Wei Liu

Recent advancements in text-to-video models such as Sora, Gen-3, MovieGen, and CogVideoX are pushing the boundaries of synthetic video generation, with adoption seen in fields like robotics, autonomous driving, and entertainment. As these…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 S P Sharan , Minkyu Choi , Sahil Shah , Harsh Goel , Mohammad Omama , Sandeep Chinchali

Text-to-video (T2V) generation technology holds potential to transform multiple domains such as education, marketing, entertainment, and assistive technologies for individuals with visual or reading comprehension challenges, by creating…

Graphics · Computer Science 2025-10-07 Nilay Kumar , Priyansh Bhandari , G. Maragatham

In recent years, text-to-image (T2I) generation models have made significant progress in generating high-quality images that align with text descriptions. However, these models also face the risk of unsafe generation, potentially producing…

Cryptography and Security · Computer Science 2025-04-16 Huming Qiu , Guanxu Chen , Mi Zhang , Xiaohan Zhang , Xiaoyu You , Min Yang

The increasing deployment of Large Vision-Language Models (LVLMs) raises safety concerns under potential malicious inputs. However, existing multimodal safety evaluations primarily focus on model vulnerabilities exposed by static image…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Xuannan Liu , Zekun Li , Zheqi He , Peipei Li , Shuhan Xia , Xing Cui , Huaibo Huang , Xi Yang , Ran He
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