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We present Vista4D, a robust and flexible video reshooting framework that grounds the input video and target cameras in a 4D point cloud. Specifically, given an input video, our method re-synthesizes the scene with the same dynamics from a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Kuan Heng Lin , Zhizheng Liu , Pablo Salamanca , Yash Kant , Ryan Burgert , Yuancheng Xu , Koichi Namekata , Yiwei Zhao , Bolei Zhou , Micah Goldblum , Paul Debevec , Ning Yu

This paper aims to tackle the challenge of dynamic view synthesis from multi-view videos. The key observation is that while previous grid-based methods offer consistent rendering, they fall short in capturing appearance details of a complex…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Haotong Lin , Sida Peng , Zhen Xu , Tao Xie , Xingyi He , Hujun Bao , Xiaowei Zhou

3D scene generation seeks to synthesize spatially structured, semantically meaningful, and photorealistic environments for applications such as immersive media, robotics, autonomous driving, and embodied AI. Early methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Beichen Wen , Haozhe Xie , Zhaoxi Chen , Fangzhou Hong , Ziwei Liu

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

Creating deformable 3D content has gained increasing attention with the rise of text-to-image and image-to-video generative models. While these models provide rich semantic priors for appearance, they struggle to capture the physical…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Jixuan He , Chieh Hubert Lin , Lu Qi , Ming-Hsuan Yang

Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric priors, their performance significantly degrades in dynamic environments. This…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Ying Zang , Xuanyi Liu , Yidong Han , Deyi Ji , Chaotao Ding , Yuanqi Hu , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

Synthesizing novel views from monocular videos of dynamic scenes remains a challenging problem. Scene-specific methods that optimize 4D representations with explicit motion priors often break down in highly dynamic regions where multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Thomas Tanay , Mohammed Brahimi , Michal Nazarczuk , Qingwen Zhang , Sibi Catley-Chandar , Arthur Moreau , Zhensong Zhang , Eduardo Pérez-Pellitero

Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, image-to-video, amongst others. Therefore, these fragmented…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xiang Fan , Sharath Girish , Vivek Ramanujan , Chaoyang Wang , Ashkan Mirzaei , Petr Sushko , Aliaksandr Siarohin , Sergey Tulyakov , Ranjay Krishna

We introduce the first approach to solve the challenging problem of unsupervised 4D visual scene understanding for complex dynamic scenes with multiple interacting people from multi-view video. Our approach simultaneously estimates a…

Computer Vision and Pattern Recognition · Computer Science 2019-07-24 Armin Mustafa , Chris Russell , Adrian Hilton

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang

World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely image-based forecasting or reasoning over partial 3D geometry, limiting their ability to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jiaxu Wang , Yicheng Jiang , Tianlun He , Jingkai Sun , Qiang Zhang , Junhao He , Jiahang Cao , Zesen Gan , Mingyuan Sun , Qiming Shao , Xiangyu Yue

World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent video generation models have demonstrated impressive visual…

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

Reconstructing dynamic 4D scenes is an important yet challenging task. While 3D foundation models like VGGT excel in static settings, they often struggle with dynamic sequences where motion causes significant geometric ambiguity. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Ying Zang , Yidong Han , Chaotao Ding , Yuanqi Hu , Deyi Ji , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

We present I2V3D, a novel framework for animating static images into dynamic videos with precise 3D control, leveraging the strengths of both 3D geometry guidance and advanced generative models. Our approach combines the precision of a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Zhiyuan Zhang , Dongdong Chen , Jing Liao

With the rapid development of 3D reconstruction technology, research in 4D reconstruction is also advancing, existing 4D reconstruction methods can generate high-quality 4D scenes. However, due to the challenges in acquiring multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Ling Yang , Kaixin Zhu , Juanxi Tian , Bohan Zeng , Mingbao Lin , Hongjuan Pei , Wentao Zhang , Shuicheng Yan

Camera-controlled generative video re-rendering methods, such as ReCamMaster, have achieved remarkable progress. However, despite their success in single-view setting, these works often struggle to maintain consistency across multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Xiao Fu , Shitao Tang , Min Shi , Xian Liu , Jinwei Gu , Ming-Yu Liu , Dahua Lin , Chen-Hsuan Lin

Modeling dynamic 3D scenes is challenging due to their high-dimensional nature, which requires aggregating information from multiple views to reconstruct time-evolving 3D geometry and motion. We present a novel multi-video 4D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Yonghan Lee , Tsung-Wei Huang , Shiv Gehlot , Jaehoon Choi , Guan-Ming Su , Dinesh Manocha

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein