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We are living in a flourishing era of digital media, where everyone has the potential to become a personal filmmaker. Current research on video generation suggests a promising avenue for controllable film creation in pixel space using…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Weiliang Chen , Fangfu Liu , Diankun Wu , Haowen Sun , Jiwen Lu , Yueqi Duan

We present FlexTraj, a framework for image-to-video generation with flexible point trajectory control. FlexTraj introduces a unified point-based motion representation that encodes each point with a segmentation ID, a temporally consistent…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Zhiyuan Zhang , Can Wang , Dongdong Chen , Jing Liao

Recent advances in large reconstruction and generative models have significantly improved scene reconstruction and novel view generation. However, due to compute limitations, each inference with these large models is confined to a small…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangjin Zhai , Zhichao Ye , Jialin Liu , Weijian Xie , Jiaqi Hu , Zhen Peng , Hua Xue , Danpeng Chen , Xiaomeng Wang , Lei Yang , Nan Wang , Haomin Liu , Guofeng Zhang

This paper presents a new method to synthesize an image from arbitrary views and times given a collection of images of a dynamic scene. A key challenge for the novel view synthesis arises from dynamic scene reconstruction where epipolar…

Computer Vision and Pattern Recognition · Computer Science 2020-04-06 Jae Shin Yoon , Kihwan Kim , Orazio Gallo , Hyun Soo Park , Jan Kautz

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D object and scene generation, they still fall short of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Xingyi Li , Yizheng Wu , Jun Cen , Juewen Peng , Kewei Wang , Ke Xian , Zhe Wang , Zhiguo Cao , Guosheng Lin

While 2D generative adversarial networks have enabled high-resolution image synthesis, they largely lack an understanding of the 3D world and the image formation process. Thus, they do not provide precise control over camera viewpoint or…

Computer Vision and Pattern Recognition · Computer Science 2021-03-31 Katja Schwarz , Yiyi Liao , Michael Niemeyer , Andreas Geiger

Recent advancements in diffusion models have revolutionized video generation, enabling the creation of high-quality, temporally consistent videos. However, generating high frame-rate (FPS) videos remains a significant challenge due to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Geunmin Hwang , Hyun-kyu Ko , Younghyun Kim , Seungryong Lee , Eunbyung Park

Multi-view diffusion models have shown promise in 3D novel view synthesis, but most existing methods adopt a non-autoregressive formulation. This limits their applicability in world modeling, as they only support a fixed number of views and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Xin Kong , Daniel Watson , Yannick Strümpler , Michael Niemeyer , Federico Tombari

The rapid evolution of video generation has enabled models to simulate complex physical dynamics and long-horizon causalities, positioning them as potential world simulators. However, a critical gap still remains between the theoretical…

Image and Video Processing · Electrical Eng. & Systems 2026-05-06 Muyang He , Hanzhong Guo , Junxiong Lin , Yizhou Yu

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

Learning object-centric representations from unsupervised videos is challenging. Unlike most previous approaches that focus on decomposing 2D images, we present a 3D generative model named DynaVol-S for dynamic scenes that enables…

Computer Vision and Pattern Recognition · Computer Science 2025-02-17 Yanpeng Zhao , Yiwei Hao , Siyu Gao , Yunbo Wang , Xiaokang Yang

Generating 3D meshes from a single image is an important but ill-posed task. Existing methods mainly adopt 2D multiview diffusion models to generate intermediate multiview images, and use the Large Reconstruction Model (LRM) to create the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Qiao Yu , Xianzhi Li , Yuan Tang , Xu Han , Long Hu , Yixue Hao , Min Chen

Human video synthesis aims to create lifelike characters in various environments, with wide applications in VR, storytelling, and content creation. While 2D diffusion-based methods have made significant progress, they struggle to generalize…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Liyuan Cui , Xiaogang Xu , Wenqi Dong , Zesong Yang , Hujun Bao , Zhaopeng Cui

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

Generating high-quality 3D characters from single images remains a significant challenge in digital content creation, particularly due to complex body poses and self-occlusion. In this paper, we present RCM (Rotate your Character Model), an…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Jin Wang , Jianxiang Lu , Comi Chen , Guangzheng Xu , Haoyu Yang , Peng Chen , Na Zhang , Yifan Xu , Longhuang Wu , Shuai Shao , Qinglin Lu , Ping Luo

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

Reconstructing 3D scenes from a single image is a fundamentally ill-posed task due to the severely under-constrained nature of the problem. Consequently, when the scene is rendered from novel camera views, existing single image to 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Sarosij Bose , Arindam Dutta , Sayak Nag , Junge Zhang , Jiachen Li , Konstantinos Karydis , Amit K. Roy Chowdhury

The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360$^{\circ}$ scene generation pipeline that facilitates the creation of comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Shijie Zhou , Zhiwen Fan , Dejia Xu , Haoran Chang , Pradyumna Chari , Tejas Bharadwaj , Suya You , Zhangyang Wang , Achuta Kadambi

Novel view synthesis from a single image has been a cornerstone problem for many Virtual Reality applications that provide immersive experiences. However, most existing techniques can only synthesize novel views within a limited range of…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Hung-Yu Tseng , Qinbo Li , Changil Kim , Suhib Alsisan , Jia-Bin Huang , Johannes Kopf

Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes. However, existing text-to-3D generation methods are limited to producing 3D objects with…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Jingbo Zhang , Xiaoyu Li , Ziyu Wan , Can Wang , Jing Liao