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While recent advances in Gaussian Splatting have enabled fast reconstruction of high-quality 3D scenes from images, extracting accurate surface meshes remains a challenge. Current approaches extract the surface through costly…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Antoine Guédon , Diego Gomez , Nissim Maruani , Bingchen Gong , George Drettakis , Maks Ovsjanikov

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

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

Decompositional reconstruction of 3D scenes, with complete shapes and detailed texture of all objects within, is intriguing for downstream applications but remains challenging, particularly with sparse views as input. Recent approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Junfeng Ni , Yu Liu , Ruijie Lu , Zirui Zhou , Song-Chun Zhu , Yixin Chen , Siyuan Huang

Reconstructing semantic-aware 3D scenes from sparse views is a challenging yet essential research direction, driven by the demands of emerging applications such as virtual reality and embodied AI. Existing per-scene optimization methods…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Yanbo Wang , Ziyi Wang , Wenzhao Zheng , Jie Zhou , Jiwen Lu

We propose \textbf{DMV3D}, a novel 3D generation approach that uses a transformer-based 3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model incorporates a triplane NeRF representation and can denoise…

Computer Vision and Pattern Recognition · Computer Science 2023-11-16 Yinghao Xu , Hao Tan , Fujun Luan , Sai Bi , Peng Wang , Jiahao Li , Zifan Shi , Kalyan Sunkavalli , Gordon Wetzstein , Zexiang Xu , Kai Zhang

3D Gaussian inpainting, a critical technique for numerous applications in virtual reality and multimedia, has made significant progress with pretrained diffusion models. However, ensuring multi-view consistency, an essential requirement for…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yuxin Cheng , Binxiao Huang , Taiqiang Wu , Wenyong Zhou , Chenchen Ding , Zhengwu Liu , Graziano Chesi , Ngai Wong

As a promising 3D generation technique, multiview diffusion (MVD) has received a lot of attention due to its advantages in terms of generalizability, quality, and efficiency. By finetuning pretrained large image diffusion models with 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Xin-Yang Zheng , Hao Pan , Yu-Xiao Guo , Xin Tong , Yang Liu

3D human reconstruction from a single image is a challenging problem and has been exclusively studied in the literature. Recently, some methods have resorted to diffusion models for guidance, optimizing a 3D representation via Score…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Kaiqiang Xiong , Rui Peng , Jiahao Wu , Zhanke Wang , Jie Liang , Xiaoyun Zheng , Feng Gao , Ronggang Wang

Image restoration (IR) has been an indispensable and challenging task in the low-level vision field, which strives to improve the subjective quality of images distorted by various forms of degradation. Recently, the diffusion model has…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Xin Li , Yulin Ren , Xin Jin , Cuiling Lan , Xingrui Wang , Wenjun Zeng , Xinchao Wang , Zhibo Chen

Recently, the emergence of diffusion models has opened up new opportunities for single-view reconstruction. However, all the existing methods represent the target object as a closed mesh devoid of any structural information, thus neglecting…

Graphics · Computer Science 2024-05-28 Anran Liu , Cheng Lin , Yuan Liu , Xiaoxiao Long , Zhiyang Dou , Hao-Xiang Guo , Ping Luo , Wenping Wang

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

We introduce a novel, training-free system for reconstructing, understanding, and rendering 3D indoor scenes from a sparse set of unposed RGB images. Unlike traditional radiance field approaches that require dense views and per-scene…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Jiatong Xia , Lingqiao Liu

3D vision systems are fundamentally constrained by their reliance on visual overlap: reconstruction methods require it for geometric alignment, while generative models use it to enforce multi-view consistency. This limitation is…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Grzegorz Wilczynski , Mikołaj Zielinski , Bartosz Świrta , Dominik Belter , Przemysław Spurek

The success of image generative models has enabled us to build methods that can edit images based on text or other user input. However, these methods are bespoke, imprecise, require additional information, or are limited to only 2D image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Rahul Sajnani , Jeroen Vanbaar , Jie Min , Kapil Katyal , Srinath Sridhar

Video diffusion models lack explicit geometric supervision during training, leading to inconsistency artifacts such as object deformation, spatial drift, and depth violations in generated videos. To address this limitation, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Tengjiao Yin , Jinglei Shi , Heng Guo , Xi Wang

Multiview diffusion models have rapidly emerged as a powerful tool for content creation with spatial consistency across viewpoints, offering rich visual realism without requiring explicit geometry and appearance representation. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Hubert Kompanowski , Varun Jampani , Aaryaman Vasishta , Binh-Son Hua

While diffusion models have demonstrated remarkable progress in 2D image generation and editing, extending these capabilities to 3D editing remains challenging, particularly in maintaining multi-view consistency. Classical approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yufeng Chi , Huimin Ma , Kafeng Wang , Jianmin Li

Novel-view synthesis through diffusion models has demonstrated remarkable potential for generating diverse and high-quality images. Yet, the independent process of image generation in these prevailing methods leads to challenges in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-01 Xianghui Yang , Yan Zuo , Sameera Ramasinghe , Loris Bazzani , Gil Avraham , Anton van den Hengel

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