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We introduce SeeingSounds, a lightweight and modular framework for audio-to-image generation that leverages the interplay between audio, language, and vision-without requiring any paired audio-visual data or training on visual generative…

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

With the rapid advancement and widespread adoption of VR/AR technologies, there is a growing demand for the creation of high-quality, immersive dynamic scenes. However, existing generation works predominantly concentrate on the creation of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Ke Xing , Hanwen Liang , Dejia Xu , Yuyang Yin , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

Real-time synthesis of high-fidelity 3D character motion from audio is a pivotal component for next-generation interactive avatars and virtual assistants. However, most existing approaches are limited to offline processing of complete audio…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Bohong Chen , Yumeng Li , Yinglin Xu , Youyi Zheng , Yanlin Weng , Kun Zhou

4D driving simulation is essential for developing realistic autonomous driving simulators. Despite advancements in existing methods for generating driving scenes, significant challenges remain in view transformation and spatial-temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Lening Wang , Wenzhao Zheng , Dalong Du , Yunpeng Zhang , Yilong Ren , Han Jiang , Zhiyong Cui , Haiyang Yu , Jie Zhou , Jiwen Lu , Shanghang Zhang

Due to the fascinating generative performance of text-to-image diffusion models, growing text-to-3D generation works explore distilling the 2D generative priors into 3D, using the score distillation sampling (SDS) loss, to bypass the data…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yu-Jie Yuan , Leif Kobbelt , Jiwen Liu , Yuan Zhang , Pengfei Wan , Yu-Kun Lai , Lin Gao

We study the problem of synthesizing a long-term dynamic video from only a single image. This is challenging since it requires consistent visual content movements given large camera motions. Existing methods either hallucinate inconsistent…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Liao Shen , Xingyi Li , Huiqiang Sun , Juewen Peng , Ke Xian , Zhiguo Cao , Guosheng Lin

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

In recent years, the increasing demand for dynamic 3D assets in design and gaming applications has given rise to powerful generative pipelines capable of synthesizing high-quality 4D objects. Previous methods generally rely on score…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qi Sun , Zhiyang Guo , Ziyu Wan , Jing Nathan Yan , Shengming Yin , Wengang Zhou , Jing Liao , Houqiang Li

Sound plays a crucial role in enhancing user experience and immersiveness in Augmented Reality (AR). However, current platforms lack support for AR sound authoring due to limited interaction types, challenges in collecting and specifying…

Human-Computer Interaction · Computer Science 2024-08-13 Xia Su , Jon E. Froehlich , Eunyee Koh , Chang Xiao

We introduce Follow-Your-Creation, a novel 4D video creation framework capable of both generating and editing 4D content from a single monocular video input. By leveraging a powerful video inpainting foundation model as a generative prior,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Yue Ma , Kunyu Feng , Xinhua Zhang , Hongyu Liu , David Junhao Zhang , Jinbo Xing , Yinhan Zhang , Ayden Yang , Zeyu Wang , Qifeng Chen

High-quality 4D reconstruction enables photorealistic and immersive rendering of the dynamic real world. However, unlike static scenes that can be fully captured with a single camera, high-quality dynamic scenes typically require dense…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weihong Pan , Xiaoyu Zhang , Zhuang Zhang , Zhichao Ye , Nan Wang , Haomin Liu , Guofeng Zhang

We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson

4D generation, or dynamic 3D content generation, integrates spatial, temporal, and view dimensions to model realistic dynamic scenes, playing a foundational role in advancing world models and physical AI. However, maintaining long-chain…

Graphics · Computer Science 2026-04-01 Yuanbin Man , Ying Huang , Zhile Ren , Miao Yin

Can machines recording an audio-visual scene produce realistic, matching audio-visual experiences at novel positions and novel view directions? We answer it by studying a new task -- real-world audio-visual scene synthesis -- and a…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Susan Liang , Chao Huang , Yapeng Tian , Anurag Kumar , Chenliang Xu

The recent success of the generative model shows that leveraging the multi-modal embedding space can manipulate an image using text information. However, manipulating an image with other sources rather than text, such as sound, is not easy…

Graphics · Computer Science 2021-12-02 Seung Hyun Lee , Wonseok Roh , Wonmin Byeon , Sang Ho Yoon , Chan Young Kim , Jinkyu Kim , Sangpil Kim

Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent systems. Recent approaches have improved temporal coherence…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Melonie de Almeida , Daniela Ivanova , Tong Shi , John H. Williamson , Paul Henderson

The generation of high-quality 3D environments is crucial for industries such as gaming, virtual reality, and cinema, yet remains resource-intensive due to the reliance on manual processes. This study performs a systematic review of…

Graphics · Computer Science 2025-06-09 Miguel Silva , Alexandre Valle de Carvalho

We present SELDVisualSynth, a tool for generating synthetic videos for audio-visual sound event localization and detection (SELD). Our approach incorporates real-world background images to improve realism in synthetic audio-visual SELD data…

Sound · Computer Science 2025-04-07 Adrian S. Roman , Aiden Chang , Gerardo Meza , Iran R. Roman

Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeling and encounter challenges in integrating diverse prior…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiyu Zhang , Xinyuan Chen , Yaohui Wang , Xihui Liu , Yunhong Wang , Yu Qiao
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