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We introduce Genie, the first generative interactive environment trained in an unsupervised manner from unlabelled Internet videos. The model can be prompted to generate an endless variety of action-controllable virtual worlds described…

We capitalize on large amounts of unlabeled video in order to learn a model of scene dynamics for both video recognition tasks (e.g. action classification) and video generation tasks (e.g. future prediction). We propose a generative…

Computer Vision and Pattern Recognition · Computer Science 2016-10-27 Carl Vondrick , Hamed Pirsiavash , Antonio Torralba

We present SceneFactor, a diffusion-based approach for large-scale 3D scene generation that enables controllable generation and effortless editing. SceneFactor enables text-guided 3D scene synthesis through our factored diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Alexey Bokhovkin , Quan Meng , Shubham Tulsiani , Angela Dai

Generating videos with realistic and physically plausible motion is one of the main recent challenges in computer vision. While diffusion models are achieving compelling results in image generation, video diffusion models are limited by…

Machine Learning · Computer Science 2024-10-28 Luca Savant Aira , Antonio Montanaro , Emanuele Aiello , Diego Valsesia , Enrico Magli

Autonomous-driving simulators typically trade physical fidelity for scalable parallelism. Physics-based platforms such as CARLA and MetaDrive provide articulated vehicle dynamics and contact, but their non-vectorized interfaces make batched…

Multiagent Systems · Computer Science 2026-05-12 Yicheng Zhu , Yang Chen , Tao Li , Zilin Bian

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a real-time framework for infinite, 3D-consistent video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ke Zhang , Yiqun Mei , Jiacong Xu , Vishal M. Patel

Controllability, temporal coherence, and detail synthesis remain the most critical challenges in video generation. In this paper, we focus on a commonly used yet underexplored cinematic technique known as Frame In and Frame Out.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Boyang Wang , Xuweiyi Chen , Matheus Gadelha , Zezhou Cheng

We introduce the concept of a generative infinite game, a video game that transcends the traditional boundaries of finite, hard-coded systems by using generative models. Inspired by James P. Carse's distinction between finite and infinite…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Jialu Li , Yuanzhen Li , Neal Wadhwa , Yael Pritch , David E. Jacobs , Michael Rubinstein , Mohit Bansal , Nataniel Ruiz

Video generation requires synthesizing consistent and persistent frames with dynamic content over time. This work investigates modeling the temporal relations for composing video with arbitrary length, from a few frames to even infinite,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-15 Qihang Zhang , Ceyuan Yang , Yujun Shen , Yinghao Xu , Bolei Zhou

Motion generation, the task of synthesizing realistic motion sequences from various conditioning inputs, has become a central problem in computer vision, computer graphics, and robotics, with applications ranging from animation and virtual…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Aliasghar Khani , Arianna Rampini , Bruno Roy , Larasika Nadela , Noa Kaplan , Evan Atherton , Derek Cheung , Jacky Bibliowicz

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

Procedurally generated video game content has the potential to drastically reduce the content creation budget of game developers and large studios. However, adoption is hindered by limitations such as slow generation, as well as low quality…

Neural and Evolutionary Computing · Computer Science 2022-04-15 Michael Beukman , Christopher W Cleghorn , Steven James

Recent advances in diffusion models bring new vitality to visual content creation. However, current text-to-video generation models still face significant challenges such as high training costs, substantial data requirements, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sicong Feng , Jielong Yang , Li Peng

In this work, we enable gamers to share their gaming experience on social media by automatically generating eye-catching highlight reels from their gameplay session Our automation will save time for gamers while increasing audience…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Vignesh Edithal , Le Zhang , Ilia Blank , Imran Junejo

Generating sound effects for videos often requires creating artistic sound effects that diverge significantly from real-life sources and flexible control in the sound design. To address this problem, we introduce MultiFoley, a model…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ziyang Chen , Prem Seetharaman , Bryan Russell , Oriol Nieto , David Bourgin , Andrew Owens , Justin Salamon

The open-domain video generation models are constrained by the scale of the training video datasets, and some less common actions still cannot be generated. Some researchers explore video editing methods and achieve action generation by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Jianzhi Liu , Junchen Zhu , Lianli Gao , Heng Tao Shen , Jingkuan Song

Real-world videos naturally portray complex interactions among distinct physical objects, effectively forming dynamic compositions of visual elements. However, most current video generation models synthesize scenes holistically and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Guofeng Zhang , Angtian Wang , Jacob Zhiyuan Fang , Liming Jiang , Haotian Yang , Alan Yuille , Chongyang Ma

Video world models have shown immense promise for interactive simulation and entertainment, but current systems still struggle with two important aspects of interactivity: user control over the environment for reproducible, editable…

Artificial Intelligence · Computer Science 2026-04-01 Ryan Po , David Junhao Zhang , Amir Hertz , Gordon Wetzstein , Neal Wadhwa , Nataniel Ruiz

The escalating quality of video generated by advanced video generation methods results in new security challenges, while there have been few relevant research efforts: 1) There is no open-source dataset for generated video detection, 2) No…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Long Ma , Zhiyuan Yan , Qinglang Guo , Yong Liao , Haiyang Yu , Pengyuan Zhou