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Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding excessive compute demands by training a diffusion model in a compressed lower-dimensional latent space. Here, we apply the LDM paradigm to high-resolution…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Andreas Blattmann , Robin Rombach , Huan Ling , Tim Dockhorn , Seung Wook Kim , Sanja Fidler , Karsten Kreis

The impressive achievements of generative models in creating high-quality videos have raised concerns about digital integrity and privacy vulnerabilities. Recent works of AI-generated content detection have been widely studied in the image…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Qingyuan Liu , Yun-Yun Tsai , Ruijian Zha , Victoria Li , Pengyuan Shi , Chengzhi Mao , Junfeng Yang

The recently developed Sora model [1] has exhibited remarkable capabilities in video generation, sparking intense discussions regarding its ability to simulate real-world phenomena. Despite its growing popularity, there is a lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Xuanyi Li , Daquan Zhou , Chenxu Zhang , Shaodong Wei , Qibin Hou , Ming-Ming Cheng

The rapid advancements in AI technologies have revolutionized the production of graphical content across various sectors, including entertainment, advertising, and e-commerce. These developments have spurred the need for robust evaluation…

Human-Computer Interaction · Computer Science 2024-09-04 Memoona Aziz , Umair Rehman , Syed Ali Safi , Amir Zaib Abbasi

Recent advances in generative artificial intelligence (AI) have captured worldwide attention. Tools such as Dalle-2 and ChatGPT suggest that tasks previously thought to be beyond the capabilities of AI may now augment the productivity of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Daniel Leiker , Ashley Ricker Gyllen , Ismail Eldesouky , Mutlu Cukurova

The Fr\'echet Video Distance (FVD) is a widely adopted metric for evaluating video generation distribution quality. However, its effectiveness relies on critical assumptions. Our analysis reveals three significant limitations: (1) the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Ge Ya Luo , Gian Mario Favero , Zhi Hao Luo , Alexia Jolicoeur-Martineau , Christopher Pal

Recent advances in generative AI have led to the development of techniques to generate visually realistic synthetic video. While a number of techniques have been developed to detect AI-generated synthetic images, in this paper we show that…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Danial Samadi Vahdati , Tai D. Nguyen , Aref Azizpour , Matthew C. Stamm

Embodied AI and robotic systems increasingly depend on scalable, diverse, and physically grounded 3D content for simulation-based training and real-world deployment. While 3D generative modeling has advanced rapidly, embodied applications…

Robotics · Computer Science 2026-05-11 Tianwei Ye , Yifan Mao , Minwen Liao , Jian Liu , Chunchao Guo , Dazhao Du , Quanxin Shou , Fangqi Zhu , Song Guo

Textured high-fidelity 3D models are crucial for games, AR/VR, and film, but human-aligned evaluation methods still fall behind despite recent advances in 3D reconstruction and generation. Existing metrics, such as Chamfer Distance, often…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Tianyu Luan , Xuelu Feng , Zixin Zhu , Phani Nuney , Sheng Liu , Xuan Gong , David Doermann , Chunming Qiao , Junsong Yuan

Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Zilong Chen , Yikai Wang , Feng Wang , Zhengyi Wang , Huaping Liu

Recent advances in AI-generated content have fueled the rise of highly realistic synthetic videos, posing severe risks to societal trust and digital integrity. Existing benchmarks for video authenticity detection typically suffer from…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Jieyu Li , Xin Zhang , Joey Tianyi Zhou

AI video generation is evolving rapidly. For video generators to be useful for applications ranging from robotics to film-making, they must consistently produce realistic videos. However, evaluating the realism of generated videos remains a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Bhavik Chandna , Kelsey R. Allen

Understanding and replicating the real world is a critical challenge in Artificial General Intelligence (AGI) research. To achieve this, many existing approaches, such as world models, aim to capture the fundamental principles governing the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Yuqi Hu , Longguang Wang , Xian Liu , Ling-Hao Chen , Yuwei Guo , Yukai Shi , Ce Liu , Anyi Rao , Zeyu Wang , Hui Xiong

World models and video generation are pivotal technologies in the domain of autonomous driving, each playing a critical role in enhancing the robustness and reliability of autonomous systems. World models, which simulate the dynamics of…

Artificial Intelligence · Computer Science 2024-11-06 Ao Fu , Yi Zhou , Tao Zhou , Yi Yang , Bojun Gao , Qun Li , Guobin Wu , Ling Shao

The advancement of generation models has led to the emergence of highly realistic artificial intelligence (AI)-generated videos. Malicious users can easily create non-existent videos to spread false information. This letter proposes an…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Jianfa Bai , Man Lin , Gang Cao

The growing prevalence of realistic AI-generated videos on media platforms increasingly blurs the line between fact and fiction, eroding public trust. Understanding how people watch AI-generated videos offers a human-centered perspective…

Human-Computer Interaction · Computer Science 2026-05-12 Danqing Shi , Lan Jiang , Katherine M. Collins , Shangzhe Wu , Ayush Tewari , Miri Zilka

With the rapid advancement of generative models, highly realistic image synthesis has posed new challenges to digital security and media credibility. Although AI-generated image detection methods have partially addressed these concerns, a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Chunxiao Li , Xiaoxiao Wang , Meiling Li , Boming Miao , Peng Sun , Yunjian Zhang , Xiangyang Ji , Yao Zhu

Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we use for training and how to ensure multi-view consistency.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Qi Zuo , Xiaodong Gu , Lingteng Qiu , Yuan Dong , Zhengyi Zhao , Weihao Yuan , Rui Peng , Siyu Zhu , Zilong Dong , Liefeng Bo , Qixing Huang

A recent frontier in computer vision has been the task of 3D video generation, which consists of generating a time-varying 3D representation of a scene. To generate dynamic 3D scenes, current methods explicitly model 3D temporal dynamics by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Rishab Parthasarathy , Zachary Ankner , Aaron Gokaslan

Automatically generating training supervision for embodied tasks is crucial, as manual designing is tedious and not scalable. While prior works use large language models (LLMs) or vision-language models (VLMs) to generate rewards, these…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Xiaowen Qiu , Yian Wang , Jiting Cai , Zhehuan Chen , Chunru Lin , Tsun-Hsuan Wang , Chuang Gan