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Recent 3D novel view synthesis (NVS) methods often require extensive 3D data for training, and also typically lack generalization beyond the training distribution. Moreover, they tend to be object centric and struggle with complex and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Taewon Kang , Divya Kothandaraman , Dinesh Manocha , Ming C. Lin

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

The generation of medical images presents significant challenges due to their high-resolution and three-dimensional nature. Existing methods often yield suboptimal performance in generating high-quality 3D medical images, and there is…

Image and Video Processing · Electrical Eng. & Systems 2025-12-02 Haoshen Wang , Zhentao Liu , Kaicong Sun , Xiaodong Wang , Dinggang Shen , Zhiming Cui

Existing multi-view 3D object reconstruction methods heavily rely on sufficient overlap between input views, where occlusions and sparse coverage in practice frequently yield severe reconstruction incompleteness. Recent advancements in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jiahao Chang , Chongjie Ye , Yushuang Wu , Yuantao Chen , Yidan Zhang , Zhongjin Luo , Chenghong Li , Yihao Zhi , Xiaoguang Han

Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation. Currently, two primary paradigms dominate the field of text-to-3D: the feed-forward generation solutions, capable of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Yonghao Yu , Shunan Zhu , Huai Qin , Haorui Li

In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation fidelity and strong generalizability. Previous methods based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Kailu Wu , Fangfu Liu , Zhihan Cai , Runjie Yan , Hanyang Wang , Yating Hu , Yueqi Duan , Kaisheng Ma

Diffusion models have recently gained recognition for generating diverse and high-quality content, especially in image synthesis. These models excel not only in creating fixed-size images but also in producing panoramic images. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xiaoyu Zhang , Teng Zhou , Xinlong Zhang , Jia Wei , Yongchuan Tang

3D image reconstruction from a limited number of 2D images has been a long-standing challenge in computer vision and image analysis. While deep learning-based approaches have achieved impressive performance in this area, existing deep…

Computer Vision and Pattern Recognition · Computer Science 2023-10-04 Nivetha Jayakumar , Tonmoy Hossain , Miaomiao Zhang

Text-to-image diffusion models have made significant progress in image generation, allowing for effortless customized generation. However, existing image editing methods still face certain limitations when dealing with personalized image…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Yuhong Zhang , Han Wang , Yiwen Wang , Rong Xie , Li Song

Recent unified 3D generation models have made remarkable progress in producing high-quality 3D assets from a single image. Notably, layout-aware approaches such as SAM3D can reconstruct multiple objects while preserving their spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Baicheng Li , Dong Wu , Jun Li , Shunkai Zhou , Zecui Zeng , Lusong Li , Hongbin Zha

Large image diffusion models enable novel view synthesis with high quality and excellent zero-shot capability. However, such models based on image-to-image translation have no guarantee of view consistency, limiting the performance for…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Haohan Weng , Tianyu Yang , Jianan Wang , Yu Li , Tong Zhang , C. L. Philip Chen , Lei Zhang

Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed. However, a challenge arises when the specific appearances need customizing at designated viewpoints but referring…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Junkai Yan , Yipeng Gao , Qize Yang , Xihan Wei , Xuansong Xie , Ancong Wu , Wei-Shi Zheng

Recently, text-to-3D approaches have achieved high-fidelity 3D content generation using text description. However, the generated objects are stochastic and lack fine-grained control. Sketches provide a cheap approach to introduce such…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Minglin Chen , Weihao Yuan , Yukun Wang , Zhe Sheng , Yisheng He , Zilong Dong , Liefeng Bo , Yulan Guo

Text-to-image diffusion models pre-trained on billions of image-text pairs have recently enabled 3D content creation by optimizing a randomly initialized differentiable 3D representation with score distillation. However, the optimization…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Yukun Huang , Jianan Wang , Yukai Shi , Boshi Tang , Xianbiao Qi , Lei Zhang

Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fangfu Liu , Wenqiang Sun , Hanyang Wang , Yikai Wang , Haowen Sun , Junliang Ye , Jun Zhang , Yueqi Duan

Recent advancements in open-world 3D object generation have been remarkable, with image-to-3D methods offering superior fine-grained control over their text-to-3D counterparts. However, most existing models fall short in simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2023-11-15 Minghua Liu , Ruoxi Shi , Linghao Chen , Zhuoyang Zhang , Chao Xu , Xinyue Wei , Hansheng Chen , Chong Zeng , Jiayuan Gu , Hao Su

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, we aim to enhance the quality and functionality of these…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xiyi Chen , Marko Mihajlovic , Shaofei Wang , Sergey Prokudin , Siyu Tang

Creating novel images by fusing visual cues from multiple sources is a fundamental yet underexplored problem in image-to-image generation, with broad applications in artistic creation, virtual reality and visual media. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Zeren Xiong , Yue Yu , Zedong Zhang , Shuo Chen , Jian Yang , Jun Li

Open-world 3D generation has recently attracted considerable attention. While many single-image-to-3D methods have yielded visually appealing outcomes, they often lack sufficient controllability and tend to produce hallucinated regions that…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Chao Xu , Ang Li , Linghao Chen , Yulin Liu , Ruoxi Shi , Hao Su , Minghua Liu
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