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This work investigates text-to-texture synthesis using diffusion models to generate physically-based texture maps. We aim to achieve realistic model appearances under varying lighting conditions. A prominent solution for the task is score…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Mishan Aliev , Dmitry Baranchuk , Kirill Struminsky

Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generation, diffusion-based scene generation, and large language…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Yian Wang , Xiaowen Qiu , Jiageng Liu , Zhehuan Chen , Jiting Cai , Yufei Wang , Tsun-Hsuan Wang , Zhou Xian , Chuang Gan

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D approaches often grapple with challenges such as…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yiwen Chen , Chi Zhang , Xiaofeng Yang , Zhongang Cai , Gang Yu , Lei Yang , Guosheng Lin

We present Text2Room, a method for generating room-scale textured 3D meshes from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image models to synthesize a sequence of images from different poses. In order to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Lukas Höllein , Ang Cao , Andrew Owens , Justin Johnson , Matthias Nießner

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

This paper aims to recover the intrinsic reflectance layer and shading layer given a single image. Though this intrinsic image decomposition problem has been studied for decades, it remains a significant challenge in cases of complex…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Xiaodong Wang , Zijun He , Xin Yuan

Recent advancements in text-to-3D generation technology have significantly advanced the conversion of textual descriptions into imaginative well-geometrical and finely textured 3D objects. Despite these developments, a prevalent limitation…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Zexiang Liu , Yangguang Li , Youtian Lin , Xin Yu , Sida Peng , Yan-Pei Cao , Xiaojuan Qi , Xiaoshui Huang , Ding Liang , Wanli Ouyang

The advancement of generative radiance fields has pushed the boundary of 3D-aware image synthesis. Motivated by the observation that a 3D object should look realistic from multiple viewpoints, these methods introduce a multi-view constraint…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Xingang Pan , Xudong Xu , Chen Change Loy , Christian Theobalt , Bo Dai

Despite the availability of large-scale 3D datasets and advancements in 3D generative models, the complexity and uneven quality of 3D geometry and texture data continue to hinder the performance of 3D generation techniques. In most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Xin Yang , Jiantao Lin , Yingjie Xu , Haodong Li , Yingcong Chen

Numerous methods have been proposed for probabilistic generative modelling of 3D objects. However, none of these is able to produce textured objects, which renders them of limited use for practical tasks. In this work, we present the first…

Computer Vision and Pattern Recognition · Computer Science 2020-04-10 Paul Henderson , Vagia Tsiminaki , Christoph H. Lampert

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Patch-based methods and deep networks have been employed to tackle image inpainting problem, with their own strengths and weaknesses. Patch-based methods are capable of restoring a missing region with high-quality texture through searching…

Computer Vision and Pattern Recognition · Computer Science 2021-11-05 Rui Xu , Minghao Guo , Jiaqi Wang , Xiaoxiao Li , Bolei Zhou , Chen Change Loy

Texture cues on 3D objects are key to compelling visual representations, with the possibility to create high visual fidelity with inherent spatial consistency across different views. Since the availability of textured 3D shapes remains very…

Computer Vision and Pattern Recognition · Computer Science 2022-04-07 Yawar Siddiqui , Justus Thies , Fangchang Ma , Qi Shan , Matthias Nießner , Angela Dai

While recent 3D generative models can produce high-quality texture images, they often fail to capture human preferences or meet task-specific requirements. Moreover, a core challenge in the 3D texture generation domain is that most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 AmirHossein Zamani , Tianhao Xie , Amir G. Aghdam , Tiberiu Popa , Eugene Belilovsky

With the rising imaging resolution of handheld devices, existing multi-exposure image fusion algorithms struggle to generate a high dynamic range image with ultra-high resolution in real-time. Apart from that, there is a trend to design a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Xin Su , Zhuoran Zheng

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

3D scene generation has quickly become a challenging new research direction, fueled by consistent improvements of 2D generative diffusion models. Most prior work in this area generates scenes by iteratively stitching newly generated frames…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Paul Engstler , Andrea Vedaldi , Iro Laina , Christian Rupprecht

This paper presents an extension to the KinectFusion algorithm which allows creating simplified 3D models with high quality RGB textures. This is achieved through (i) creating model textures using images from an HD RGB camera that is…

Graphics · Computer Science 2016-02-23 Song Liu , Wanqing Li , Philip Ogunbona , Yang-Wai Chow

High-quality 3D streaming from multiple cameras is crucial for immersive experiences in many AR/VR applications. The limited number of views - often due to real-time constraints - leads to missing information and incomplete surfaces in the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Leif Van Holland , Domenic Zingsheim , Mana Takhsha , Hannah Dröge , Patrick Stotko , Markus Plack , Reinhard Klein

Texture editing is a crucial task in 3D modeling that allows users to automatically manipulate the surface materials of 3D models. However, the inherent complexity of 3D models and the ambiguous text description lead to the challenge in…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Shengqi Liu , Zhuo Chen , Jingnan Gao , Yichao Yan , Wenhan Zhu , Jiangjing Lyu , Xiaokang Yang