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The introduction of neural radiance fields has greatly improved the effectiveness of view synthesis for monocular videos. However, existing algorithms face difficulties when dealing with uncontrolled or lengthy scenarios, and require…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Kaichen Zhou , Jia-Xing Zhong , Sangyun Shin , Kai Lu , Yiyuan Yang , Andrew Markham , Niki Trigoni

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

This paper presents DualCamCtrl, a novel end-to-end diffusion model for camera-controlled video generation. Recent works have advanced this field by representing camera poses as ray-based conditions, yet they often lack sufficient scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Hongfei Zhang , Kanghao Chen , Zixin Zhang , Harold Haodong Chen , Yuanhuiyi Lyu , Yuqi Zhang , Shuai Yang , Kun Zhou , Yingcong Chen

The remarkable capabilities of pretrained image diffusion models have been utilized not only for generating fixed-size images but also for creating panoramas. However, naive stitching of multiple images often results in visible seams.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Yuseung Lee , Kunho Kim , Hyunjin Kim , Minhyuk Sung

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

A recent frontier in computer vision has been the task of 3D video generation, which consists of generating a time-varying 3D representation of a scene. To generate dynamic 3D scenes, current methods explicitly model 3D temporal dynamics by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Rishab Parthasarathy , Zachary Ankner , Aaron Gokaslan

High-quality driving video generation is crucial for providing training data for autonomous driving models. However, current generative models rarely focus on enhancing camera motion control under multi-view tasks, which is essential for…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Yining Yao , Xi Guo , Chenjing Ding , Wei Wu

This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works that lack support for unified shared world construction with multi-agent interaction. ShareVerse…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiayi Zhu , Jianing Zhang , Yiying Yang , Wei Cheng , Xiaoyun Yuan

Interactive video generation has significant potential for scene simulation and video creation. However, existing methods often struggle with maintaining scene consistency during long video generation under dynamic camera control due to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Xinhang Gao , Junlin Guan , Shuhan Luo , Wenzhuo Li , Guanghuan Tan , Jiacheng Wang

Recent video generation models demonstrate impressive synthesis capabilities but remain limited by single-modality conditioning, constraining their holistic world understanding. This stems from insufficient cross-modal interaction and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jiehui Huang , Yuechen Zhang , Xu He , Yuan Gao , Zhi Cen , Bin Xia , Yan Zhou , Xin Tao , Pengfei Wan , Jiaya Jia

Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consistency in highly dynamic real-world environments. In this work, we introduce \textbf{AnyView}, a…

Recently video diffusion models have emerged as expressive generative tools for high-quality video content creation readily available to general users. However, these models often do not offer precise control over camera poses for video…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Dejia Xu , Weili Nie , Chao Liu , Sifei Liu , Jan Kautz , Zhangyang Wang , Arash Vahdat

Camera-controlled video-to-video (V2V) generation enables dynamic viewpoint synthesis from monocular footage, holding immense potential for interactive filmmaking and live broadcasting. However, existing implicit synthesis methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Youcan Xu , Jiaxin Shi , Zhen Wang , Wensong Song , Feifei Shao , Chen Liang , Jun Xiao , Long Chen

With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye

Accurate reconstruction of complex dynamic scenes from just a single viewpoint continues to be a challenging task in computer vision. Current dynamic novel view synthesis methods typically require videos from many different camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Basile Van Hoorick , Rundi Wu , Ege Ozguroglu , Kyle Sargent , Ruoshi Liu , Pavel Tokmakov , Achal Dave , Changxi Zheng , Carl Vondrick

In this work, we present CineMaster, a novel framework for 3D-aware and controllable text-to-video generation. Our goal is to empower users with comparable controllability as professional film directors: precise placement of objects within…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Qinghe Wang , Yawen Luo , Xiaoyu Shi , Xu Jia , Huchuan Lu , Tianfan Xue , Xintao Wang , Pengfei Wan , Di Zhang , Kun Gai

World models based on video generation demonstrate remarkable potential for simulating interactive environments but face persistent difficulties in two key areas: maintaining long-term content consistency when scenes are revisited and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianxing Xu , Zixuan Wang , Guangyuan Wang , Li Hu , Zhongyi Zhang , Peng Zhang , Bang Zhang , Song-Hai Zhang

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

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCrafter}, a novel method for synthesizing high-fidelity novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Wangbo Yu , Jinbo Xing , Li Yuan , Wenbo Hu , Xiaoyu Li , Zhipeng Huang , Xiangjun Gao , Tien-Tsin Wong , Ying Shan , Yonghong Tian

3D panorama synthesis is a promising yet challenging task that demands high-quality and diverse visual appearance and geometry of the generated omnidirectional content. Existing methods leverage rich image priors from pre-trained 2D…

Graphics · Computer Science 2025-06-23 Yukun Huang , Yanning Zhou , Jianan Wang , Kaiyi Huang , Xihui Liu