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Related papers: MVPainter: Accurate and Detailed 3D Texture Genera…

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Reconstructing 3D human faces in the wild with the 3D Morphable Model (3DMM) has become popular in recent years. While most prior work focuses on estimating more robust and accurate geometry, relatively little attention has been paid to…

Graphics · Computer Science 2020-11-26 Myunggi Lee , Wonwoong Cho , Moonheum Kim , David Inouye , Nojun Kwak

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem

There has recently been great interest in neural rendering methods. Some approaches use 3D geometry reconstructed with Multi-View Stereo (MVS) but cannot recover from the errors of this process, while others directly learn a volumetric…

Computer Vision and Pattern Recognition · Computer Science 2021-09-09 Georgios Kopanas , Julien Philip , Thomas Leimkühler , George Drettakis

Recently, 3D generation methods have shown their powerful ability to automate 3D model creation. However, most 3D generation methods only rely on an input image or a text prompt to generate a 3D model, which lacks the control of each…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Peng Li , Suizhi Ma , Jialiang Chen , Yuan Liu , Congyi Zhang , Wei Xue , Wenhan Luo , Alla Sheffer , Wenping Wang , Yike Guo

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

Textures are a vital aspect of creating visually appealing and realistic 3D models. In this paper, we study the problem of generating high-fidelity texture given shapes of 3D assets, which has been relatively less explored compared with…

Computer Vision and Pattern Recognition · Computer Science 2023-10-09 An-Chieh Cheng , Xueting Li , Sifei Liu , Xiaolong Wang

Recent research on texture synthesis for 3D shapes benefits a lot from dramatically developed 2D text-to-image diffusion models, including inpainting-based and optimization-based approaches. However, these methods ignore the modal gap…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Shang Liu , Chaohui Yu , Chenjie Cao , Wen Qian , Fan Wang

Diffusion generative models have recently greatly improved the power of text-conditioned image generation. Existing image generation models mainly include text conditional diffusion model and cross-modal guided diffusion model, which are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Wei Li , Xue Xu , Xinyan Xiao , Jiachen Liu , Hu Yang , Guohao Li , Zhanpeng Wang , Zhifan Feng , Qiaoqiao She , Yajuan Lyu , Hua Wu

The field of photorealistic 3D avatar reconstruction and generation has garnered significant attention in recent years; however, animating such avatars remains challenging. Recent advances in diffusion models have notably enhanced the…

This paper introduces a novel approach to synthesize texture to dress up a given 3D object, given a text prompt. Based on the pretrained text-to-image (T2I) diffusion model, existing methods usually employ a project-and-inpaint approach, in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Yuxin Liu , Minshan Xie , Hanyuan Liu , Tien-Tsin Wong

3D scene generation is in high demand across various domains, including virtual reality, gaming, and the film industry. Owing to the powerful generative capabilities of text-to-image diffusion models that provide reliable priors, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Haiyang Zhou , Xinhua Cheng , Wangbo Yu , Yonghong Tian , Li Yuan

We present TexFusion (Texture Diffusion), a new method to synthesize textures for given 3D geometries, using large-scale text-guided image diffusion models. In contrast to recent works that leverage 2D text-to-image diffusion models to…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Tianshi Cao , Karsten Kreis , Sanja Fidler , Nicholas Sharp , Kangxue Yin

Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV images into consistent 3D objects. However, the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Yizheng Chen , Rengan Xie , Qi Ye , Sen Yang , Zixuan Xie , Tianxiao Chen , Rong Li , Yuchi Huo

Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing ControlNet-like methods struggle with compositional visual conditioning - simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Yanjie Pan , Qingdong He , Zhengkai Jiang , Pengcheng Xu , Chaoyi Wang , Jinlong Peng , Haoxuan Wang , Yun Cao , Zhenye Gan , Mingmin Chi , Bo Peng , Yabiao Wang

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu

Recent advances in 3D generation have been remarkable, with methods such as DreamFusion leveraging large-scale text-to-image diffusion-based models to guide 3D object generation. These methods enable the synthesis of detailed and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Bohan Zeng , Shanglin Li , Yutang Feng , Ling Yang , Hong Li , Sicheng Gao , Jiaming Liu , Conghui He , Wentao Zhang , Jianzhuang Liu , Baochang Zhang , Shuicheng Yan

Multi-view projection techniques have shown themselves to be highly effective in achieving top-performing results in the recognition of 3D shapes. These methods involve learning how to combine information from multiple view-points. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Abdullah Hamdi , Faisal AlZahrani , Silvio Giancola , Bernard Ghanem

We present a topology-informed inverse rendering approach for reconstructing high-genus surface meshes from multi-view images. Compared to 3D representations like voxels and point clouds, mesh-based representations are preferred as they…

Diffusion models have shown great promise for image generation, beating GANs in terms of generation diversity, with comparable image quality. However, their application to 3D shapes has been limited to point or voxel representations that…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Gimin Nam , Mariem Khlifi , Andrew Rodriguez , Alberto Tono , Linqi Zhou , Paul Guerrero
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