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We introduce abstract rendering, a method for computing a set of images by rendering a scene from a continuously varying range of camera positions. The resulting abstract image-which encodes an infinite collection of possible renderings-is…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yangge Li , Chenxi Ji , Xiangru Zhong , Huan Zhang , Sayan Mitra

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

Generating 3D worlds from text is a highly anticipated goal in computer vision. Existing works are limited by the degree of exploration they allow inside of a scene, i.e., produce streched-out and noisy artifacts when moving beyond central…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Manuel-Andreas Schneider , Lukas Höllein , Matthias Nießner

We present a method for relighting 3D reconstructions of large room-scale environments. Existing solutions for 3D scene relighting often require solving under-determined or ill-conditioned inverse rendering problems, and are as such unable…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Xiaoyan Xing , Philipp Henzler , Junhwa Hur , Runze Li , Jonathan T. Barron , Pratul P. Srinivasan , Dor Verbin

Generating multi-camera street-view videos is critical for augmenting autonomous driving datasets, addressing the urgent demand for extensive and varied data. Due to the limitations in diversity and challenges in handling lighting…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Jiachen Lu , Ze Huang , Zeyu Yang , Jiahui Zhang , Li Zhang

Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural rendering approaches achieve high-fidelity rendering along the recorded trajectories,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Henry Che , Jingkang Wang , Yun Chen , Ze Yang , Sivabalan Manivasagam , Raquel Urtasun

Scene-level 3D generation represents a critical frontier in multimedia and computer graphics, yet existing approaches either suffer from limited object categories or lack editing flexibility for interactive applications. In this paper, we…

Graphics · Computer Science 2025-04-18 Wenqi Dong , Bangbang Yang , Zesong Yang , Yuan Li , Tao Hu , Hujun Bao , Yuewen Ma , Zhaopeng Cui

Generating large-scale 3D scenes cannot simply apply existing 3D object synthesis technique since 3D scenes usually hold complex spatial configurations and consist of a number of objects at varying scales. We thus propose a practical and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Qihang Zhang , Yinghao Xu , Yujun Shen , Bo Dai , Bolei Zhou , Ceyuan Yang

Recent text-to-image models have revolutionized image generation, but they still struggle with maintaining concept consistency across generated images. While existing works focus on character consistency, they often overlook the crucial…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Quanjian Song , Donghao Zhou , Jingyu Lin , Fei Shen , Jiaze Wang , Xiaowei Hu , Cunjian Chen , Pheng-Ann Heng

Implicit neural representations have demonstrated significant promise for 3D scene reconstruction. Recent works have extended their applications to autonomous implicit reconstruction through the Next Best View (NBV) based method. However,…

Robotics · Computer Science 2024-04-17 Jing Zeng , Yanxu Li , Jiahao Sun , Qi Ye , Yunlong Ran , Jiming Chen

Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffusion show promise in navigating these goals, especially when…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Can Qin , Shu Zhang , Ning Yu , Yihao Feng , Xinyi Yang , Yingbo Zhou , Huan Wang , Juan Carlos Niebles , Caiming Xiong , Silvio Savarese , Stefano Ermon , Yun Fu , Ran Xu

Image generation today can produce somewhat realistic images from text prompts. However, if one asks the generator to synthesize a specific camera setting such as creating different fields of view using a 24mm lens versus a 70mm lens, the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Yu Yuan , Xijun Wang , Yichen Sheng , Prateek Chennuri , Xingguang Zhang , Stanley Chan

Recent advances in driving-scene generation and reconstruction have demonstrated significant potential for enhancing autonomous driving systems by producing scalable and controllable training data. Existing generation methods primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Ziyue Zhu , Zhanqian Wu , Zhenxin Zhu , Lijun Zhou , Haiyang Sun , Bing Wan , Kun Ma , Guang Chen , Hangjun Ye , Jin Xie , jian Yang

Sequence generation models have recently made significant progress in unifying various vision tasks. Although some auto-regressive models have demonstrated promising results in end-to-end text spotting, they use specific detection formats…

Computer Vision and Pattern Recognition · Computer Science 2023-04-10 Taeho Kil , Seonghyeon Kim , Sukmin Seo , Yoonsik Kim , Daehee Kim

The scarcity of free-hand sketch presents a challenging problem. Despite the emergence of some large-scale sketch datasets, these datasets primarily consist of sketches at the single-object level. There continues to be a lack of large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zhenbei Wu , Qiang Wang , Jie Yang

Compositing an object into an image involves multiple non-trivial sub-tasks such as object placement and scaling, color/lighting harmonization, viewpoint/geometry adjustment, and shadow/reflection generation. Recent generative image…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Gemma Canet Tarrés , Zhe Lin , Zhifei Zhang , Jianming Zhang , Yizhi Song , Dan Ruta , Andrew Gilbert , John Collomosse , Soo Ye Kim

Scene graph generation has received growing attention with the advancements in image understanding tasks such as object detection, attributes and relationship prediction,~\etc. However, existing datasets are biased in terms of object and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Jiuxiang Gu , Handong Zhao , Zhe Lin , Sheng Li , Jianfei Cai , Mingyang Ling

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Outdoor scene reconstruction remains challenging due to the stark contrast between well-textured, nearby regions and distant backgrounds dominated by low detail, uneven illumination, and sky effects. We introduce a two-stage Gaussian…

Graphics · Computer Science 2025-10-13 Deborah Pintani , Ariel Caputo , Noah Lewis , Marc Stamminger , Fabio Pellacini , Andrea Giachetti

With recent developments in Embodied Artificial Intelligence (EAI) research, there has been a growing demand for high-quality, large-scale interactive scene generation. While prior methods in scene synthesis have prioritized the naturalness…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yandan Yang , Baoxiong Jia , Peiyuan Zhi , Siyuan Huang