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We propose a method for constructing generative models of 3D objects from a single 3D mesh and improving them through unsupervised low-shot learning from 2D images. Our method produces a 3D morphable model that represents shape and albedo…

Computer Vision and Pattern Recognition · Computer Science 2022-03-08 Skylar Sutherland , Bernhard Egger , Joshua Tenenbaum

Grasping is an important human activity that has long been studied in robotics, computer vision, and cognitive science. Most existing works study grasping from the perspective of synthesizing hand poses conditioned on 3D or 2D object…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Chaerin Min , Srinath Sridhar

In this paper, we explore the existing challenges in 3D artistic scene generation by introducing ART3D, a novel framework that combines diffusion models and 3D Gaussian splatting techniques. Our method effectively bridges the gap between…

Computer Vision and Pattern Recognition · Computer Science 2024-05-20 Pengzhi Li , Chengshuai Tang , Qinxuan Huang , Zhiheng Li

Three-dimensional content generation has progressed from producing isolated, visually plausible shapes to constructing structured assets that can be deployed in real-time interactive environments. This trajectory is driven by converging…

Graphics · Computer Science 2026-05-12 Jiafeng Wu , Zhuofan Lou , Jian Liu , Dazhao Du , Chunchao Guo , Song Guo

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

Most advances in 3D Generative Adversarial Networks (3D GANs) largely depend on ray casting-based volume rendering, which incurs demanding rendering costs. One promising alternative is rasterization-based 3D Gaussian Splatting (3D-GS),…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Sangeek Hyun , Jae-Pil Heo

We are interested in learning visual representations which allow for 3D manipulations of visual objects based on a single 2D image. We cast this into an image-to-image transformation task, and propose Iterative Generative Adversarial…

Computer Vision and Pattern Recognition · Computer Science 2019-09-05 Ysbrand Galama , Thomas Mensink

Generative artificial intelligence has recently progressed from static image and video synthesis to 3D content generation, culminating in the emergence of 4D generation-the task of synthesizing temporally coherent dynamic 3D assets guided…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Qiaowei Miao , Kehan Li , Jinsheng Quan , Zhiyuan Min , Shaojie Ma , Yichao Xu , Yi Yang , Ping Liu , Yawei Luo

3D Gaussian Splatting (3DGS) enables high-quality real-time 3D rendering but faces challenges in efficiently scaling to ultra-dense scenes and high-resolution due to computational bottlenecks that limit its use in latency-sensitive…

Graphics · Computer Science 2026-05-13 Yibo Zhao , Fan Gao , Youcheng Cai , Ligang Liu

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, demonstrating remarkable capability in high-fidelity scene reconstruction through its Gaussian primitive representations. However, the computational…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Chengbo Wang , Guozheng Ma , Yifei Xue , Yizhen Lao

We consider the problem of editing 3D objects and scenes based on open-ended language instructions. A common approach to this problem is to use a 2D image generator or editor to guide the 3D editing process, obviating the need for 3D data.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Minghao Chen , Iro Laina , Andrea Vedaldi

While text-to-3D and image-to-3D generation tasks have received considerable attention, one important but under-explored field between them is controllable text-to-3D generation, which we mainly focus on in this work. To address this task,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Zhiqi Li , Yiming Chen , Lingzhe Zhao , Peidong Liu

Building articulated objects is a key challenge in computer vision. Existing methods often fail to effectively integrate information across different object states, limiting the accuracy of part-mesh reconstruction and part dynamics…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Yu Liu , Baoxiong Jia , Ruijie Lu , Junfeng Ni , Song-Chun Zhu , Siyuan Huang

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

Recent advancements in 3D content generation from text or a single image struggle with limited high-quality 3D datasets and inconsistency from 2D multi-view generation. We introduce DiffSplat, a novel 3D generative framework that natively…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Chenguo Lin , Panwang Pan , Bangbang Yang , Zeming Li , Yadong Mu

Recent advancements in Text-to-3D modeling have shown significant potential for the creation of 3D content. However, due to the complex geometric shapes of objects in the natural world, generating 3D content remains a challenging task.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Huanning Dong , Fan Li , Ping Kuang , Jianwen Min

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in synthesizing novel views after training on a given set of viewpoints. However, its rendering quality deteriorates when the synthesized view deviates significantly from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Jiatong Xia , Lingqiao Liu

Fast generation of high-quality 3D digital humans is important to a vast number of applications ranging from entertainment to professional concerns. Recent advances in differentiable rendering have enabled the training of 3D generative…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Zhangyang Xiong , Di Kang , Derong Jin , Weikai Chen , Linchao Bao , Shuguang Cui , Xiaoguang Han

3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage requirements and inherently unstructured representation pose challenges for deployment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Yuqin Lu , Yang Zhou , Yihua Dai , Guiqing Li , Shengfeng He

Generating 3D scenes from natural language holds great promise for applications in gaming, film, and design. However, existing methods struggle with automation, 3D consistency, and fine-grained control. We present DreamScene, an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Haoran Li , Yuli Tian , Kun Lan , Yong Liao , Lin Wang , Pan Hui , Peng Yuan Zhou
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