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Related papers: Yan: Foundational Interactive Video Generation

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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

Customized video generation aims to produce videos featuring specific subjects under flexible user-defined conditions, yet existing methods often struggle with identity consistency and limited input modalities. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Teng Hu , Zhentao Yu , Zhengguang Zhou , Sen Liang , Yuan Zhou , Qin Lin , Qinglin Lu

The rapid evolution of video generation has enabled models to simulate complex physical dynamics and long-horizon causalities, positioning them as potential world simulators. However, a critical gap still remains between the theoretical…

Image and Video Processing · Electrical Eng. & Systems 2026-05-06 Muyang He , Hanzhong Guo , Junxiong Lin , Yizhou Yu

This paper proposes a novel model for video generation and especially makes the attempt to deal with the problem of video generation from text descriptions, i.e., synthesizing realistic videos conditioned on given texts. Existing video…

Computer Vision and Pattern Recognition · Computer Science 2020-08-14 Hongyuan Yu , Yan Huang , Lihong Pi , Liang Wang

We present a novel unconditional video generative model designed to address long-term spatial and temporal dependencies, with attention to computational and dataset efficiency. To capture long spatio-temporal dependencies, our approach…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Partha Ghosh , Soubhik Sanyal , Cordelia Schmid , Bernhard Schölkopf

With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video generation foundation models has led to growing demand for…

Foundational world models must be both interactive and preserve spatiotemporal coherence for effective future planning with action choices. However, present models for long video generation have limited inherent world modeling capabilities…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Taiye Chen , Xun Hu , Zihan Ding , Chi Jin

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Text-to-Video generation, which utilizes the provided text prompt to generate high-quality videos, has drawn increasing attention and achieved great success due to the development of diffusion models recently. Existing methods mainly rely…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zirui Pan , Xin Wang , Yipeng Zhang , Hong Chen , Kwan Man Cheng , Yaofei Wu , Wenwu Zhu

Generative AI is transforming image synthesis, enabling the creation of high-quality, diverse, and photorealistic visuals across industries like design, media, healthcare, and autonomous systems. Advances in techniques such as…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Fouad Bousetouane

Modern game development faces significant challenges in creativity and cost due to predetermined content in traditional game engines. Recent breakthroughs in video generation models, capable of synthesizing realistic and interactive virtual…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Jiwen Yu , Yiran Qin , Haoxuan Che , Quande Liu , Xintao Wang , Pengfei Wan , Di Zhang , Xihui Liu

The landscape of video generation is shifting, from a focus on generating visually appealing clips to building virtual environments that support interaction and maintain physical plausibility. These developments point toward the emergence…

Artificial Intelligence · Computer Science 2026-02-09 Jingtong Yue , Ziqi Huang , Zhaoxi Chen , Xintao Wang , Pengfei Wan , Ziwei Liu

Technological developments have produced methods that can generate educational videos from input text or sound. Recently, the use of deep learning techniques for image and video generation has been widely explored, particularly in…

Multimedia · Computer Science 2026-01-27 M. E. ElAlami , S. M. Khater , M. El. R. Rehan

While diffusion model for audio-driven avatar video generation have achieved notable process in synthesizing long sequences with natural audio-visual synchronization and identity consistency, the generation of music-performance videos with…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Jiahui Chen , Weida Wang , Runhua Shi , Huan Yang , Chaofan Ding , Zihao Chen

Interactive Generative Video (IGV) has emerged as a crucial technology in response to the growing demand for high-quality, interactive video content across various domains. In this paper, we define IGV as a technology that combines…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Jiwen Yu , Yiran Qin , Haoxuan Che , Quande Liu , Xintao Wang , Pengfei Wan , Di Zhang , Kun Gai , Hao Chen , Xihui Liu

In the dynamic field of digital content creation using generative models, state-of-the-art video editing models still do not offer the level of quality and control that users desire. Previous works on video editing either extended from…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Max Ku , Cong Wei , Weiming Ren , Harry Yang , Wenhu Chen

Diffusion models have emerged as a powerful generative method for synthesizing high-quality and diverse set of images. In this paper, we propose a video generation method based on diffusion models, where the effects of motion are modeled in…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Kangfu Mei , Vishal M. Patel

Generative AI assistants have been widely used in front-end programming. However, besides code writing, developers often encounter the need to generate animation effects. As novices in creative design without the assistance of professional…

Human-Computer Interaction · Computer Science 2025-06-30 Tianrun Qiu , Yuxin Ma

AI-generated content has attracted lots of attention recently, but photo-realistic video synthesis is still challenging. Although many attempts using GANs and autoregressive models have been made in this area, the visual quality and length…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Yingqing He , Tianyu Yang , Yong Zhang , Ying Shan , Qifeng Chen

Recent advances in generative world models have enabled remarkable progress in creating open-ended game environments, evolving from static scene synthesis toward dynamic, interactive simulation. However, current approaches remain limited by…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Junshu Tang , Jiacheng Liu , Jiaqi Li , Longhuang Wu , Haoyu Yang , Penghao Zhao , Siruis Gong , Xiang Yuan , Shuai Shao , Linfeng Zhang , Qinglin Lu