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Related papers: TexPro: Text-guided PBR Texturing with Procedural …

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The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Hongkun Zhang , Zherong Pan , Congyi Zhang , Lifeng Zhu , Xifeng Gao

We present Make-A-Texture, a new framework that efficiently synthesizes high-resolution texture maps from textual prompts for given 3D geometries. Our approach progressively generates textures that are consistent across multiple viewpoints…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Xiaoyu Xiang , Liat Sless Gorelik , Yuchen Fan , Omri Armstrong , Forrest Iandola , Yilei Li , Ita Lifshitz , Rakesh Ranjan

Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmented reality (AR), virtual reality (VR), and extended reality (XR). Nevertheless, current…

Robotics · Computer Science 2026-04-22 Seok Joon Kim , Dinh Duc Cao , Federica Spinola , Se Jin Lee , Kyu Sung Cho

In this work, we develop intuitive controls for editing the style of 3D objects. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which conform to a target text prompt. We consider a disentangled…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Oscar Michel , Roi Bar-On , Richard Liu , Sagie Benaim , Rana Hanocka

We present Meta 3D AssetGen (AssetGen), a significant advancement in text-to-3D generation which produces faithful, high-quality meshes with texture and material control. Compared to works that bake shading in the 3D object's appearance,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Yawar Siddiqui , Tom Monnier , Filippos Kokkinos , Mahendra Kariya , Yanir Kleiman , Emilien Garreau , Oran Gafni , Natalia Neverova , Andrea Vedaldi , Roman Shapovalov , David Novotny

Physically-based rendering (PBR) materials are fundamental to photorealistic graphics, yet their creation remains labor-intensive and requires specialized expertise. While generative models have advanced material synthesis, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Di Luo , Shuhui Yang , Mingxin Yang , Jiawei Lu , Yixuan Tang , Xintong Han , Zhuo Chen , Beibei Wang , Chunchao Guo

Image super-resolution (SR) methods typically model degradation to improve reconstruction accuracy in complex and unknown degradation scenarios. However, extracting degradation information from low-resolution images is challenging, which…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zheng Chen , Yulun Zhang , Jinjin Gu , Xin Yuan , Linghe Kong , Guihai Chen , Xiaokang Yang

Handling various objects with different colors is a significant challenge for image colorization techniques. Thus, for complex real-world scenes, the existing image colorization algorithms often fail to maintain color consistency. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Subhankar Ghosh , Saumik Bhattacharya , Prasun Roy , Umapada Pal , Michael Blumenstein

Monocular 3D object detection typically relies on pseudo-labeling techniques to reduce dependency on real-world annotations. Recent advances demonstrate that deterministic linguistic cues can serve as effective auxiliary weak supervision…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Chupeng Liu , Jiyong Rao , Shangquan Sun , Runkai Zhao , Weidong Cai

Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes. However, existing text-to-3D generation methods are limited to producing 3D objects with…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Jingbo Zhang , Xiaoyu Li , Ziyu Wan , Can Wang , Jing Liao

Photo realism in computer generated imagery is crucially dependent on how well an artist is able to recreate real-world materials in the scene. The workflow for material modeling and editing typically involves manual tweaking of material…

Graphics · Computer Science 2019-08-27 Aakash KT , Parikshit Sakurikar , Saurabh Saini , P. J. Narayanan

While physically-based rendering (PBR) simulates light transport that guarantees physical realism, achieving true photorealistic rendering (PRR) demands prohibitive time and labor, and still struggles to capture the intractable richness of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Jiayuan Lu , Rengan Xie , Xuancheng Jin , Zhizhen Wu , Qi Ye , Tian Xie , Hujun Bao , Rui Wang. Yuchi Huo

Advances in Generative AI tools have allowed designers to manipulate existing 3D models using text or image-based prompts, enabling creators to explore different design goals. Photochromic color-changing systems, on the other hand, allow…

Human-Computer Interaction · Computer Science 2024-04-29 Yunyi Zhu , Faraz Faruqi , Stefanie Mueller

3D generation methods have shown visually compelling results powered by diffusion image priors. However, they often fail to produce realistic geometric details, resulting in overly smooth surfaces or geometric details inaccurately baked in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ruihan Gao , Kangle Deng , Gengshan Yang , Wenzhen Yuan , Jun-Yan Zhu

Generating high-quality and diverse human images is an important yet challenging task in vision and graphics. However, existing generative models often fall short under the high diversity of clothing shapes and textures. Furthermore, the…

Computer Vision and Pattern Recognition · Computer Science 2022-06-01 Yuming Jiang , Shuai Yang , Haonan Qiu , Wayne Wu , Chen Change Loy , Ziwei Liu

Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositional generation. In this paper, we propose RealCompo, a new…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Xinchen Zhang , Ling Yang , Yaqi Cai , Zhaochen Yu , Kai-Ni Wang , Jiake Xie , Ye Tian , Minkai Xu , Yong Tang , Yujiu Yang , Bin Cui

Training native 3D texture generative models remains a fundamental yet challenging problem, largely due to the limited availability of large-scale, high-quality 3D texture datasets. This scarcity hinders generalization to real-world…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Ze Yuan , Xin Yu , Yangtian Sun , Yuan-Chen Guo , Yan-Pei Cao , Ding Liang , Xiaojuan Qi

Textured 3D morphing creates smooth and plausible interpolation sequences between two 3D objects, focusing on transitions in both shape and texture. This is important for creative applications like visual effects in filmmaking. Previous…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Songlin Yang , Yushi Lan , Honghua Chen , Xingang Pan

Recent advancements in generative models have enabled the creation of dynamic 4D content - 3D objects in motion - based on text prompts, which holds potential for applications in virtual worlds, media, and gaming. Existing methods provide…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Ohad Rahamim , Ori Malca , Dvir Samuel , Gal Chechik

Text-to-image models have shown remarkable progress in generating high-quality images from user-provided prompts. Despite this, the quality of these images varies due to the models' sensitivity to human language nuances. With advancements…

Artificial Intelligence · Computer Science 2024-06-14 Xinrui Yang , Zhuohan Wang , Anthony Hu
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