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Denoising diffusion models have demonstrated outstanding results in 2D image generation, yet it remains a challenge to replicate its success in 3D shape generation. In this paper, we propose leveraging multi-view depth, which represents…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zhen Wang , Qiangeng Xu , Feitong Tan , Menglei Chai , Shichen Liu , Rohit Pandey , Sean Fanello , Achuta Kadambi , Yinda Zhang

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

Diffusion models currently achieve state-of-the-art performance for both conditional and unconditional image generation. However, so far, image diffusion models do not support tasks required for 3D understanding, such as view-consistent 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Titas Anciukevičius , Zexiang Xu , Matthew Fisher , Paul Henderson , Hakan Bilen , Niloy J. Mitra , Paul Guerrero

This paper introduces KeyDiff3D, a framework for unsupervised monocular 3D keypoints estimation that accurately predicts 3D keypoints from a single image. While previous methods rely on manual annotations or calibrated multi-view images,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Subin Jeon , In Cho , Junyoung Hong , Seon Joo Kim

Diffusion models have become a mainstream approach for high-resolution image synthesis. However, directly generating higher-resolution images from pretrained diffusion models will encounter unreasonable object duplication and exponentially…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Shen Zhang , Zhaowei Chen , Zhenyu Zhao , Yuhao Chen , Yao Tang , Jiajun Liang

We introduce "ImageDream," an innovative image-prompt, multi-view diffusion model for 3D object generation. ImageDream stands out for its ability to produce 3D models of higher quality compared to existing state-of-the-art,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Peng Wang , Yichun Shi

Existing single image-to-3D creation methods typically involve a two-stage process, first generating multi-view images, and then using these images for 3D reconstruction. However, training these two stages separately leads to significant…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Hao Wen , Zehuan Huang , Yaohui Wang , Xinyuan Chen , Lu Sheng

Multi-view image generation holds significant application value in computer vision, particularly in domains like 3D reconstruction, virtual reality, and augmented reality. Most existing methods, which rely on extending single images, face…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Jiaqi Wu , Yaosen Chen , Shuyuan Zhu

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

Generating high-quality 360-degree views of human heads from single-view images is essential for enabling accessible immersive telepresence applications and scalable personalized content creation. While cutting-edge methods for full head…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yuming Gu , Phong Tran , Yujian Zheng , Hongyi Xu , Heyuan Li , Adilbek Karmanov , Hao Li

Generating consistent multiple views for 3D reconstruction tasks is still a challenge to existing image-to-3D diffusion models. Generally, incorporating 3D representations into diffusion model decrease the model's speed as well as…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Emmanuelle Bourigault , Pauline Bourigault

Diffusion Transformers (DiTs) have emerged as a leading architecture for text-to-image synthesis, producing high-quality and photorealistic images. However, the quadratic scaling properties of the attention in DiTs hinder image generation…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Philipp Becker , Abhinav Mehrotra , Ruchika Chavhan , Malcolm Chadwick , Luca Morreale , Mehdi Noroozi , Alberto Gil Ramos , Sourav Bhattacharya

Generating high-resolution images with generative models has recently been made widely accessible by leveraging diffusion models pre-trained on large-scale datasets. Various techniques, such as MultiDiffusion and SyncDiffusion, have further…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Stanislav Frolov , Brian B. Moser , Andreas Dengel

In this work, we introduce \textbf{Wonder3D++}, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Yuxiao Yang , Xiao-Xiao Long , Zhiyang Dou , Cheng Lin , Yuan Liu , Qingsong Yan , Yuexin Ma , Haoqian Wang , Zhiqiang Wu , Wei Yin

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

Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the back view) and inaccurate shapes (e.g., animals with extra…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Cheng Chen , Xiaofeng Yang , Fan Yang , Chengzeng Feng , Zhoujie Fu , Chuan-Sheng Foo , Guosheng Lin , Fayao Liu

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

We propose a novel image editing technique that enables 3D manipulations on single images, such as object rotation and translation. Existing 3D-aware image editing approaches typically rely on synthetic multi-view datasets for training…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Ruicheng Wang , Jianfeng Xiang , Jiaolong Yang , Xin Tong

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan