English
Related papers

Related papers: Quantitative Video World Model Evaluation for Geom…

200 papers

High-quality 3D world models are pivotal for embodied intelligence and Artificial General Intelligence (AGI), underpinning applications such as AR/VR content creation and robotic navigation. Despite the established strong imaginative…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Yixiang Dai , Fan Jiang , Chiyu Wang , Mu Xu , Yonggang Qi

World models serve as essential building blocks toward Artificial General Intelligence (AGI), enabling intelligent agents to predict future states and plan actions by simulating complex physical interactions. However, existing interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Junyi Chen , Haoyi Zhu , Xianglong He , Yifan Wang , Jianjun Zhou , Wenzheng Chang , Yang Zhou , Zizun Li , Zhoujie Fu , Jiangmiao Pang , Tong He

Previous works leveraging video models for image-to-3D scene generation tend to suffer from geometric distortions and blurry content. In this paper, we renovate the pipeline of image-to-3D scene generation by unlocking the potential of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuhao Wan , Lijuan Liu , Jingzhi Zhou , Zihan Zhou , Xuying Zhang , Dongbo Zhang , Shaohui Jiao , Qibin Hou , Ming-Ming Cheng

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

We introduce Vid-CamEdit, a novel framework for video camera trajectory editing, enabling the re-synthesis of monocular videos along user-defined camera paths. This task is challenging due to its ill-posed nature and the limited multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Junyoung Seo , Jisang Han , Jaewoo Jung , Siyoon Jin , Joungbin Lee , Takuya Narihira , Kazumi Fukuda , Takashi Shibuya , Donghoon Ahn , Shoukang Hu , Seungryong Kim , Yuki Mitsufuji

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

Continuous perception, the ability to integrate visual observations over time in a continuous stream fashion, is essential for robust real-world understanding, yet remains largely untested in current multimodal models. We introduce…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zeyu Wang , Zhenzhen Weng , Serena Yeung-Levy

We present a novel video generation framework that integrates 3-dimensional geometry and dynamic awareness. To achieve this, we augment 2D videos with 3D point trajectories and align them in pixel space. The resulting 3D-aware video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Yunuo Chen , Junli Cao , Vidit Goel , Sergei Korolev , Chenfanfu Jiang , Jian Ren , Sergey Tulyakov , Anil Kag

Video-conditioned 4D shape generation aims to recover time-varying 3D geometry and view-consistent appearance directly from an input video. In this work, we introduce a native video-to-4D shape generation framework that synthesizes a single…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Jiraphon Yenphraphai , Ashkan Mirzaei , Jianqi Chen , Jiaxu Zou , Sergey Tulyakov , Raymond A. Yeh , Peter Wonka , Chaoyang Wang

We present an algorithm for reconstructing dense, geometrically consistent depth for all pixels in a monocular video. We leverage a conventional structure-from-motion reconstruction to establish geometric constraints on pixels in the video.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-28 Xuan Luo , Jia-Bin Huang , Richard Szeliski , Kevin Matzen , Johannes Kopf

Video diffusion models generate high-quality and diverse worlds; however, individual frames often lack 3D consistency across the output sequence, which makes the reconstruction of 3D worlds difficult. To this end, we propose a new method…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Lukas Höllein , Matthias Nießner

Scene-consistent video generation aims to create videos that explore 3D scenes based on a camera trajectory. Previous methods rely on video generation models with external memory for consistency, or iterative 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 JiaKui Hu , Jialun Liu , Liying Yang , Xinliang Zhang , Kaiwen Li , Shuang Zeng , Yuanwei Li , Haibin Huang , Chi Zhang , Yanye Lu

Recent progress in driving video generation has shown significant potential for enhancing self-driving systems by providing scalable and controllable training data. Although pretrained state-of-the-art generation models, guided by 2D layout…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yishen Ji , Ziyue Zhu , Zhenxin Zhu , Kaixin Xiong , Ming Lu , Zhiqi Li , Lijun Zhou , Haiyang Sun , Bing Wang , Tong Lu

We introduce GeCo, a geometry-grounded metric for jointly detecting geometric deformation and occlusion-inconsistency artifacts in static scenes. By fusing residual motion and depth priors, GeCo produces interpretable, dense consistency…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Leslie Gu , Junhwa Hur , Charles Herrmann , Fangneng Zhan , Todd Zickler , Deqing Sun , Hanspeter Pfister

Recent advances in generative modeling can create remarkably realistic synthetic videos, making it increasingly difficult for humans to distinguish them from real ones and necessitating reliable detection methods. However, two key…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Long Ma , Zihao Xue , Yan Wang , Zhiyuan Yan , Jin Xu , Xiaorui Jiang , Haiyang Yu , Yong Liao , Zhen Bi

Video spatial reasoning requires accumulating viewpoint-dependent evidence over time while retaining information useful to the question being asked. Existing spatial video-language models improve geometric perception and long-range context…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Xianqiang Gao , Qizhi Chen , Delin Qu , Haoming Song , Zhigang Wang , Bin Zhao , Dong Wang , Xuelong Li

Video generation assessment is essential for ensuring that generative models produce visually realistic, high-quality videos while aligning with human expectations. Current video generation benchmarks fall into two main categories:…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Hui Han , Siyuan Li , Jiaqi Chen , Yiwen Yuan , Yuling Wu , Chak Tou Leong , Hanwen Du , Junchen Fu , Youhua Li , Jie Zhang , Chi Zhang , Li-jia Li , Yongxin Ni

Significant advancements have been made in video generative models recently. Unlike image generation, video generation presents greater challenges, requiring not only generating high-quality frames but also ensuring temporal consistency…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Jiahe Liu , Youran Qu , Qi Yan , Xiaohui Zeng , Lele Wang , Renjie Liao

We propose a new method for the visual quality assessment of 360-degree (omnidirectional) videos. The proposed method is based on computing multiple spatio-temporal objective quality features on viewports extracted from 360-degree videos. A…

Multimedia · Computer Science 2021-05-04 Roberto G. de A. Azevedo , Neil Birkbeck , Ivan Janatra , Balu Adsumilli , Pascal Frossard

Generative video models are increasingly used in design animation tasks, yet no standardized evaluation framework exists for this domain. Unlike natural video generation, design animation imposes structured constraints: specific components…

Graphics · Computer Science 2026-05-18 Adrienne Deganutti , Dingning Cao , Jaejung Seol , Elad Hirsch , Purvanshi Mehta