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We present \textsc{Vx2Text}, a framework for text generation from multimodal inputs consisting of video plus text, speech, or audio. In order to leverage transformer networks, which have been shown to be effective at modeling language, each…

Computer Vision and Pattern Recognition · Computer Science 2021-02-02 Xudong Lin , Gedas Bertasius , Jue Wang , Shih-Fu Chang , Devi Parikh , Lorenzo Torresani

Video generation models are revolutionizing content creation, with image-to-video models drawing increasing attention due to their enhanced controllability, visual consistency, and practical applications. However, despite their popularity,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Wenhao Wang , Yi Yang

Video generation has advanced rapidly, improving evaluation methods, yet assessing video's motion remains a major challenge. Specifically, there are two key issues: 1) current motion metrics do not fully align with human perceptions; 2) the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Xinran Ling , Chen Zhu , Meiqi Wu , Hangyu Li , Xiaokun Feng , Cundian Yang , Aiming Hao , Jiashu Zhu , Jiahong Wu , Xiangxiang Chu

Rapid advances in text-to-image (T2I) generation have raised higher requirements for evaluation methodologies. Existing benchmarks center on objective capabilities and dimensions, but lack an application-scenario perspective, limiting…

Artificial Intelligence · Computer Science 2025-09-23 Xiaojing Dong , Weilin Huang , Liang Li , Yiying Li , Shu Liu , Tongtong Ou , Shuang Ouyang , Yu Tian , Fengxuan Zhao

While generative models such as text-to-image, large language models and text-to-video have seen significant progress, the extension to text-to-virtual-reality remains largely unexplored, due to a deficit in training data and the complexity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Vriksha Srihari , R. Bhavya , Shruti Jayaraman , V. Mary Anita Rajam

Text-to-video (T2V) generation has recently garnered significant attention thanks to the large multi-modality model Sora. However, T2V generation still faces two important challenges: 1) Lacking a precise open sourced high-quality dataset.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Kepan Nan , Rui Xie , Penghao Zhou , Tiehan Fan , Zhenheng Yang , Zhijie Chen , Xiang Li , Jian Yang , Ying Tai

We introduce a novel diffusion-based video generation method, generating a video showing multiple events given multiple individual sentences from the user. Our method does not require a large-scale video dataset since our method uses a…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Gyeongrok Oh , Jaehwan Jeong , Sieun Kim , Wonmin Byeon , Jinkyu Kim , Sungwoong Kim , Sangpil Kim

Recent breakthroughs in Vision-Language (V&L) joint research have achieved remarkable results in various text-driven tasks. High-quality Text-to-video (T2V), a task that has been long considered mission-impossible, was proven feasible with…

Artificial Intelligence · Computer Science 2022-11-28 Yuxing Qiu , Feng Gao , Minchen Li , Govind Thattai , Yin Yang , Chenfanfu Jiang

Text-to-Video (T2V) generation has benefited from recent advances in diffusion models, yet current systems still struggle under complex scenarios, which are generally exacerbated by the ambiguity and underspecification of text prompts. In…

Artificial Intelligence · Computer Science 2026-04-21 Chengyi Yang , Pengzhen Li , Jiayin Qi , Aimin Zhou , Ji Wu , Ji Liu

Infographics are composite visual artifacts that combine data visualizations with textual and illustrative elements to communicate information. While recent text-to-image (T2I) models can generate aesthetically appealing images, their…

Exams are a fundamental test of expert-level intelligence and require integrated understanding, reasoning, and generation. Existing exam-style benchmarks mainly focus on understanding and reasoning tasks, and current generation benchmarks…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Zhaokai Wang , Penghao Yin , Xiangyu Zhao , Changyao Tian , Yu Qiao , Wenhai Wang , Jifeng Dai , Gen Luo

While recent text-to-speech (TTS) systems increasingly integrate nonverbal vocalizations (NVs), their evaluations lack standardized metrics and reliable ground-truth references. To bridge this gap, we propose NV-Bench, the first benchmark…

Sound · Computer Science 2026-03-19 Qinke Ni , Huan Liao , Dekun Chen , Yuxiang Wang , Zhizheng Wu

Text-to-image models often struggle to generate images that precisely match textual prompts. Prior research has extensively studied the evaluation of image-text alignment in text-to-image generation. However, existing evaluations primarily…

Computation and Language · Computer Science 2025-06-11 Huixuan Zhang , Xiaojun Wan

Recent advancements in personalized Text-to-Video (T2V) generation have made significant strides in synthesizing character-specific content. However, these methods face a critical limitation: the inability to perform fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Haopeng Fang , Di Qiu , Binjie Mao , He Tang

Existing text-to-video (T2V) models often struggle with generating videos with sufficiently pronounced or complex actions. A key limitation lies in the text prompt's inability to precisely convey intricate motion details. To address this,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Qiang Zhou , Shaofeng Zhang , Nianzu Yang , Ye Qian , Hao Li

Real-world video editing demands not only expert knowledge of cinematic techniques but also multimodal reasoning to select, align, and combine footage into coherent narratives. While recent Large Multimodal Models (LMMs) have shown…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Andong Deng , Dawei Du , Zhenfang Chen , Wen Zhong , Fan Chen , Guang Chen , Chia-Wen Kuo , Longyin Wen , Chen Chen , Sijie Zhu

The rapid advancement of text-to-video (T2V) models has revolutionized content creation, yet their commercial potential remains largely untapped. We introduce, for the first time, the task of seamless brand integration in T2V: automatically…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Zihao Zhu , Ruotong Wang , Siwei Lyu , Min Zhang , Baoyuan Wu

We review human evaluation practices in automatic, speech-driven 3D gesture generation and find a lack of standardisation and frequent use of flawed experimental setups. This leads to a situation where it is impossible to know how different…

Recent advances in text-to-video diffusion models have enabled the generation of high-quality videos conditioned on textual descriptions. However, most existing text-to-video models rely solely on textual conditions, lacking general…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuheng Chen , Teng Hu , Jiangning Zhang , Zhucun Xue , Ran Yi , Lizhuang Ma

Current text-to-video (T2V) generation models are increasingly popular due to their ability to produce coherent videos from textual prompts. However, these models often struggle to generate semantically and temporally consistent videos when…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Minkyu Choi , S P Sharan , Harsh Goel , Sahil Shah , Sandeep Chinchali