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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

As foundation models become more sophisticated, ensuring their trustworthiness becomes increasingly critical; yet, unlike text and image, the video modality still lacks comprehensive trustworthiness benchmarks. We introduce VMDT…

Text-to-video (T2V) diffusion models have recently achieved impressive visual quality, yet most systems still generate silent clips and treat audio as a secondary concern. Existing audio-video generation pipelines typically decompose the…

The next frontier for video generation lies in developing models capable of zero-shot reasoning, where understanding real-world scientific laws is crucial for accurate physical outcome modeling under diverse conditions. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Lanxiang Hu , Abhilash Shankarampeta , Yixin Huang , Zilin Dai , Haoyang Yu , Yujie Zhao , Haoqiang Kang , Daniel Zhao , Tajana Rosing , Hao Zhang

Text-video retrieval is a challenging task that aims to search relevant video contents based on natural language descriptions. The key to this problem is to measure text-video similarities in a joint embedding space. However, most existing…

Computer Vision and Pattern Recognition · Computer Science 2021-04-21 Xiaohan Wang , Linchao Zhu , Yi Yang

Panorama video recently attracts more interest in both study and application, courtesy of its immersive experience. Due to the expensive cost of capturing 360-degree panoramic videos, generating desirable panorama videos by prompts is…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Qian Wang , Weiqi Li , Chong Mou , Xinhua Cheng , Jian Zhang

Video generation models have significantly advanced embodied intelligence, unlocking new possibilities for generating diverse robot data that capture perception, reasoning, and action in the physical world. However, synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Yufan Deng , Zilin Pan , Hongyu Zhang , Xiaojie Li , Ruoqing Hu , Yufei Ding , Yiming Zou , Yan Zeng , Daquan Zhou

Recent advances in generative modeling can create remarkably realistic synthetic videos, making it increasingly difficult for humans to distinguish them from real ones and necessitating reliable detection methods. However, two key…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Long Ma , Zihao Xue , Yan Wang , Zhiyuan Yan , Jin Xu , Xiaorui Jiang , Haiyang Yu , Yong Liao , Zhen Bi

Text-to-3D generation has achieved remarkable progress in recent years, yet evaluating these methods remains challenging for two reasons: i) Existing benchmarks lack fine-grained evaluation on different prompt categories and evaluation…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Yujie Zhang , Bingyang Cui , Qi Yang , Zhu Li , Yiling Xu

Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models still struggle with prompts that require rich world knowledge and implicit reasoning: both of which are critical for producing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Daoan Zhang , Che Jiang , Ruoshi Xu , Biaoxiang Chen , Zijian Jin , Yutian Lu , Jianguo Zhang , Liang Yong , Jiebo Luo , Shengda Luo

While text-to-visual models now produce photo-realistic images and videos, they struggle with compositional text prompts involving attributes, relationships, and higher-order reasoning such as logic and comparison. In this work, we conduct…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Baiqi Li , Zhiqiu Lin , Deepak Pathak , Jiayao Li , Yixin Fei , Kewen Wu , Tiffany Ling , Xide Xia , Pengchuan Zhang , Graham Neubig , Deva Ramanan

Most existing video-and-language (VidL) research focuses on a single dataset, or multiple datasets of a single task. In reality, a truly useful VidL system is expected to be easily generalizable to diverse tasks, domains, and datasets. To…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Linjie Li , Jie Lei , Zhe Gan , Licheng Yu , Yen-Chun Chen , Rohit Pillai , Yu Cheng , Luowei Zhou , Xin Eric Wang , William Yang Wang , Tamara Lee Berg , Mohit Bansal , Jingjing Liu , Lijuan Wang , Zicheng Liu

Interleaved text-and-image generation has been an intriguing research direction, where the models are required to generate both images and text pieces in an arbitrary order. Despite the emerging advancements in interleaved generation, the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Minqian Liu , Zhiyang Xu , Zihao Lin , Trevor Ashby , Joy Rimchala , Jiaxin Zhang , Lifu Huang

Modern text-to-video (T2V) diffusion models can synthesize visually compelling clips, yet they remain brittle at fine-scale structure: even state-of-the-art generators often produce distorted faces and hands, warped backgrounds, and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Tejas Panambur , Ishan Rajendrakumar Dave , Chongjian Ge , Ersin Yumer , Xue Bai

Recent advancements in large multimodal models (LMMs) have driven substantial progress in both text-to-video (T2V) generation and video-to-text (V2T) interpretation tasks. However, current AI-generated videos (AIGVs) still exhibit…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Jiarui Wang , Huiyu Duan , Ziheng Jia , Yu Zhao , Woo Yi Yang , Zicheng Zhang , Zijian Chen , Juntong Wang , Yuke Xing , Guangtao Zhai , Xiongkuo Min

Text-to-video (T2V) synthesis has gained increasing attention in the community, in which the recently emerged diffusion models (DMs) have promisingly shown stronger performance than the past approaches. While existing state-of-the-art DMs…

Artificial Intelligence · Computer Science 2024-03-20 Hao Fei , Shengqiong Wu , Wei Ji , Hanwang Zhang , Tat-Seng Chua

Vector graphics are widely used in digital art and highly favored by designers due to their scalability and layer-wise properties. However, the process of creating and editing vector graphics requires creativity and design expertise, making…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Peiying Zhang , Nanxuan Zhao , Jing Liao

Recent years have witnessed an explosion of user-generated content (UGC) videos shared and streamed over the Internet, thanks to the evolution of affordable and reliable consumer capture devices, and the tremendous popularity of social…

Computer Vision and Pattern Recognition · Computer Science 2021-05-05 Zhengzhong Tu , Yilin Wang , Neil Birkbeck , Balu Adsumilli , Alan C. Bovik

The rapid growth of text-to-video (T2V) diffusion models has raised concerns about privacy, copyright, and safety due to their potential misuse in generating harmful or misleading content. These models are often trained on numerous…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Naen Xu , Jinghuai Zhang , Changjiang Li , Zhi Chen , Chunyi Zhou , Qingming Li , Tianyu Du , Shouling Ji

Online courses have significantly lowered the barrier to accessing education, yet the varying content quality of these videos poses challenges. In this work, we focus on the task of automatically evaluating the quality of video course…

Multimedia · Computer Science 2025-01-07 Xiaoxuan Zhu , Zhouhong Gu , Sihang Jiang , Zhixu Li , Hongwei Feng , Yanghua Xiao
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