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Image view synthesis has seen great success in reconstructing photorealistic visuals, thanks to deep learning and various novel representations. The next key step in immersive virtual experiences is view synthesis of dynamic scenes.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Kai-En Lin , Guowei Yang , Lei Xiao , Feng Liu , Ravi Ramamoorthi

Generative models have demonstrated remarkable abilities in generating high-fidelity visual content. In this work, we explore how generative models can further be used not only to synthesize visual content but also to understand the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Yanbo Wang , Justin Dauwels , Yilun Du

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

Recent advancements in generative models have provided promising solutions for synthesizing realistic driving videos, which are crucial for training autonomous driving perception models. However, existing approaches often struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Wei Wu , Xi Guo , Weixuan Tang , Tingxuan Huang , Chiyu Wang , Dongyue Chen , Chenjing Ding

Video frame interpolation algorithms typically estimate optical flow or its variations and then use it to guide the synthesis of an intermediate frame between two consecutive original frames. To handle challenges like occlusion,…

Computer Vision and Pattern Recognition · Computer Science 2018-03-30 Simon Niklaus , Feng Liu

Novel view synthesis (NVS) from a single image is highly ill-posed due to large unobserved regions, especially for views that deviate significantly from the input. While existing methods focus on consistency between the source and generated…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Xueyang Kang , Zhengkang Xiang , Zezheng Zhang , Kourosh Khoshelham

Diffusion models have demonstrated great success in text-to-video (T2V) generation. However, existing methods may face challenges when handling complex (long) video generation scenarios that involve multiple objects or dynamic changes in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Ye Tian , Ling Yang , Haotian Yang , Yuan Gao , Yufan Deng , Jingmin Chen , Xintao Wang , Zhaochen Yu , Xin Tao , Pengfei Wan , Di Zhang , Bin Cui

The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appealing content, they predominantly rely on sparse conditioning signals such as text prompts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Zhida Zhang , Jie Ma , Zhan Peng , Haoxue Wu , Yang Han , Jun Liang , Jie Cao , Jing Li

Despite recent progress, video diffusion models still struggle to synthesize realistic videos involving highly dynamic motions or requiring fine-grained motion controllability. A central limitation lies in the scarcity of such examples in…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Wonjoon Jin , Jiyun Won , Janghyeok Han , Qi Dai , Chong Luo , Seung-Hwan Baek , Sunghyun Cho

Scene understanding is a prerequisite to many high level tasks for any automated intelligent machine operating in real world environments. Recent attempts with supervised learning have shown promise in this direction but also highlighted…

Computer Vision and Pattern Recognition · Computer Science 2015-11-30 Ankur Handa , Viorica Patraucean , Vijay Badrinarayanan , Simon Stent , Roberto Cipolla

Acquiring detailed 3D scenes typically demands costly equipment, multi-view data, or labor-intensive modeling. Therefore, a lightweight alternative, generating complex 3D scenes from a single top-down image, plays an essential role in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Kaizhi Zheng , Ruijian Zha , Zishuo Xu , Jing Gu , Jie Yang , Xin Eric Wang

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

Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illumination, scene motion, and other unintended effects that are…

This paper introduces MetaBGM, a groundbreaking framework for generating background music that adapts to dynamic scenes and real-time user interactions. We define multi-scene as variations in environmental contexts, such as transitions in…

Sound · Computer Science 2024-09-09 Haoxuan Liu , Zihao Wang , Haorong Hong , Youwei Feng , Jiaxin Yu , Han Diao , Yunfei Xu , Kejun Zhang

Image composition aims to seamlessly insert foreground object into background. Despite the huge progress in generative image composition, the existing methods are still struggling with simultaneous detail preservation and foreground…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Jiaxuan Chen , Bo Zhang , Qingdong He , Jinlong Peng , Li Niu

There has been exciting progress in generating images from natural language or layout conditions. However, these methods struggle to faithfully reproduce complex scenes due to the insufficient modeling of multiple objects and their…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Yunnan Wang , Ziqiang Li , Zequn Zhang , Wenyao Zhang , Baao Xie , Xihui Liu , Wenjun Zeng , Xin Jin

Human vision combines low-resolution "gist" information from the visual periphery with sparse but high-resolution information from fixated locations to construct a coherent understanding of a visual scene. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Ritik Raina , Abe Leite , Alexandros Graikos , Seoyoung Ahn , Dimitris Samaras , Gregory J. Zelinsky

Novel view synthesis from a single input image is a challenging task, where the goal is to generate a new view of a scene from a desired camera pose that may be separated by a large motion. The highly uncertain nature of this synthesis task…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Jason J. Yu , Fereshteh Forghani , Konstantinos G. Derpanis , Marcus A. Brubaker

Simulation is crucial for developing and evaluating autonomous vehicle (AV) systems. Recent literature builds on a new generation of generative models to synthesize highly realistic images for full-stack simulation. However, purely…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Zehao Zhu , Yuliang Zou , Chiyu Max Jiang , Bo Sun , Vincent Casser , Xiukun Huang , Jiahao Wang , Zhenpei Yang , Ruiqi Gao , Leonidas Guibas , Mingxing Tan , Dragomir Anguelov

Our project page: https://scutyklin.github.io/SceneLCM/. Automated generation of complex, interactive indoor scenes tailored to user prompt remains a formidable challenge. While existing methods achieve indoor scene synthesis, they struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yangkai Lin , Jiabao Lei , Kui Jia