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Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt view direction and mainly handle object-centric cases. In…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yuanhao Cai , He Zhang , Kai Zhang , Yixun Liang , Mengwei Ren , Fujun Luan , Qing Liu , Soo Ye Kim , Jianming Zhang , Zhifei Zhang , Yuqian Zhou , Yulun Zhang , Xiaokang Yang , Zhe Lin , Alan Yuille

Camera-controlled video generation has achieved remarkable progress in recent years. However, existing video-to-video re-rendering methods primarily rely on Supervised Fine-Tuning using synthetic datasets. At present, there is an extreme…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Zizun Li , Haoyu Guo , Runzhe Teng , Chunhua Shen , Tong He

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

We present a diffusion-based model for 3D-aware generative novel view synthesis from as few as a single input image. Our model samples from the distribution of possible renderings consistent with the input and, even in the presence of…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Eric R. Chan , Koki Nagano , Matthew A. Chan , Alexander W. Bergman , Jeong Joon Park , Axel Levy , Miika Aittala , Shalini De Mello , Tero Karras , Gordon Wetzstein

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Recent text-to-3D methods employing diffusion models have made significant advancements in 3D human generation. However, these approaches face challenges due to the limitations of text-to-image diffusion models, which lack an understanding…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xin Huang , Ruizhi Shao , Qi Zhang , Hongwen Zhang , Ying Feng , Yebin Liu , Qing Wang

We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100$\times$ faster than previous works while possessing superior rendering quality. Our approach shifts from the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinyang Li , Tengfei Wang , Zixiao Gu , Shengchuan Zhang , Chunchao Guo , Liujuan Cao

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. Additionally, 3D scene generation is vital for advancing embodied AI and world models, which depend…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yuxin Zhang , Ziyu Lu , Hongbo Duan , Keyu Fan , Pengting Luo , Peiyu Zhuang , Mengyu Yang , Houde Liu

Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing 3D GANs are either compute-intensive or make approximations…

3D Gaussian Splatting has demonstrated superior performance in rendering efficiency and quality, yet the generation of 3D Gaussians still remains a challenge without proper geometric priors. Existing methods have explored predicting point…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Kanle Shi , Shenkun Xu , Yi Fang , Yu-Shen Liu

LiDAR-based 3D detection has made great progress in recent years. However, the performance of 3D detectors is considerably limited when deployed in unseen environments, owing to the severe domain gap problem. Existing domain adaptive 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Ziyu Li , Jingming Guo , Tongtong Cao , Liu Bingbing , Wankou Yang

Text-to-video generation has advanced rapidly in visual fidelity, whereas standard methods still have limited ability to control the subject composition of generated scenes. Prior work shows that adding localized text control signals, such…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Guofeng Zhang , Angtian Wang , Jacob Zhiyuan Fang , Liming Jiang , Haotian Yang , Bo Liu , Yiding Yang , Guang Chen , Longyin Wen , Alan Yuille , Chongyang Ma

End-to-end autonomous driving has evolved from the conventional paradigm based on sparse perception into vision-language-action (VLA) models, which focus on learning language descriptions as an auxiliary task to facilitate planning. In this…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Sicheng Zuo , Zixun Xie , Wenzhao Zheng , Shaoqing Xu , Fang Li , Hanbing Li , Long Chen , Zhi-Xin Yang , Jiwen Lu

Realistic and diverse 3D shape generation is helpful for a wide variety of applications such as virtual reality, gaming, and animation. Modern generative models, such as GANs and diffusion models, learn from large-scale datasets and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Jingyuan Zhu , Huimin Ma , Jiansheng Chen , Jian Yuan

One image to editable dynamic 3D model and video generation is novel direction and change in the research area of single image to 3D representation or 3D reconstruction of image. Gaussian Splatting has demonstrated its advantages in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinwei Lin

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Diffusion models have emerged as the new state-of-the-art generative model with high quality samples, with intriguing properties such as mode coverage and high flexibility. They have also been shown to be effective inverse problem solvers,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Hyungjin Chung , Dohoon Ryu , Michael T. McCann , Marc L. Klasky , Jong Chul Ye

Text-to-3D generation from a single-view image is a popular but challenging task in 3D vision. Although numerous methods have been proposed, existing works still suffer from the inconsistency issues, including 1) semantic inconsistency, 2)…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Yichen Ouyang , Wenhao Chai , Jiayi Ye , Dapeng Tao , Yibing Zhan , Gaoang Wang

3D Gaussian Splatting has recently emerged as an efficient solution for high-quality and real-time novel view synthesis. However, its capability for accurate surface reconstruction remains underexplored. Due to the discrete and unstructured…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Qing Li , Huifang Feng , Xun Gong , Yu-Shen Liu

Perceiving and reconstructing 3D scene geometry from visual inputs is crucial for autonomous driving. However, there still lacks a driving-targeted dense geometry perception model that can adapt to different scenarios and camera…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Sicheng Zuo , Zixun Xie , Wenzhao Zheng , Shaoqing Xu , Fang Li , Shengyin Jiang , Long Chen , Zhi-Xin Yang , Jiwen Lu