English
Related papers

Related papers: Text-guided Controllable Mesh Refinement for Inter…

200 papers

Directly generating 3D meshes, the default representation for 3D shapes in the graphics industry, using auto-regressive (AR) models has become popular these days, thanks to their sharpness, compactness in the generated results, and ability…

Graphics · Computer Science 2025-09-26 Jiabao Lei , Kewei Shi , Zhihao Liang , Kui Jia

Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable across various applications, including entertainment,…

Graphics · Computer Science 2024-12-12 Kaiwei Zhang , Dandan Zhu , Xiongkuo Min , Guangtao Zhai

We introduce MeshGPT, a new approach for generating triangle meshes that reflects the compactness typical of artist-created meshes, in contrast to dense triangle meshes extracted by iso-surfacing methods from neural fields. Inspired by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Yawar Siddiqui , Antonio Alliegro , Alexey Artemov , Tatiana Tommasi , Daniele Sirigatti , Vladislav Rosov , Angela Dai , Matthias Nießner

The requirement for 3D content is growing as AR/VR application emerges. At the same time, 3D modelling is only available for skillful experts, because traditional methods like Computer-Aided Design (CAD) are often too labor-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Ying Zang , Yidong Han , Chaotao Ding , Jianqi Zhang , Tianrun Chen

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Kai He , Chin-Hsuan Wu , Igor Gilitschenski

Current text-to-image models struggle to provide precise camera control using natural language alone. In this work, we present a framework for precise camera control with global scene understanding in text-to-image generation by learning…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Xinxuan Lu , Charless Fowlkes , Alexander C. Berg

This paper presents a new text-guided technique for generating 3D shapes. The technique leverages a hybrid 3D shape representation, namely EXIM, combining the strengths of explicit and implicit representations. Specifically, the explicit…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Zhengzhe Liu , Jingyu Hu , Ka-Hei Hui , Xiaojuan Qi , Daniel Cohen-Or , Chi-Wing Fu

Customizing pre-trained text-to-image generation model has attracted massive research interest recently, due to its huge potential in real-world applications. Although existing methods are able to generate creative content for a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yufan Zhou , Ruiyi Zhang , Jiuxiang Gu , Tong Sun

Prompt engineering is still the primary way for users of generative text-to-image models to manipulate generated images in a targeted way. Based on treating the model as a continuous function and by passing gradients between the image space…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Niklas Deckers , Julia Peters , Martin Potthast

While NeRF-based 3D-aware image generation methods enable viewpoint control, limitations still remain to be adopted to various 3D applications. Due to their view-dependent and light-entangled volume representation, the 3D geometry presents…

Computer Vision and Pattern Recognition · Computer Science 2022-03-15 Minsoo Lee , Chaeyeon Chung , Hojun Cho , Minjung Kim , Sanghun Jung , Jaegul Choo , Minhyuk Sung

We propose a training-free approach to 3D editing that enables the editing of a single shape within a few minutes. The edited 3D mesh aligns well with the prompts, and remains identical for regions that are not intended to be altered. To…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ziya Erkoç , Can Gümeli , Chaoyang Wang , Matthias Nießner , Angela Dai , Peter Wonka , Hsin-Ying Lee , Peiye Zhuang

Recent advances in image generation have achieved remarkable visual quality, while a fundamental challenge remains: Can image generation be controlled at the element level, enabling intuitive modifications such as adjusting shapes, altering…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Lanqing Guo , Xi Liu , Yufei Wang , Zhihao Li , Siyu Huang

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Liangchen Song , Liangliang Cao , Hongyu Xu , Kai Kang , Feng Tang , Junsong Yuan , Yang Zhao

Single image 3D reconstruction is an important but challenging task that requires extensive knowledge of our natural world. Many existing methods solve this problem by optimizing a neural radiance field under the guidance of 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-06-30 Minghua Liu , Chao Xu , Haian Jin , Linghao Chen , Mukund Varma T , Zexiang Xu , Hao Su

3D object generation has undergone significant advancements, yielding high-quality results. However, fall short of achieving precise user control, often yielding results that do not align with user expectations, thus limiting their…

Graphics · Computer Science 2024-04-26 Shaocong Dong , Lihe Ding , Zhanpeng Huang , Zibin Wang , Tianfan Xue , Dan Xu

Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Xingyu Ren , Alexandros Lattas , Baris Gecer , Jiankang Deng , Chao Ma , Xiaokang Yang , Stefanos Zafeiriou

We present ShaDDR, an example-based deep generative neural network which produces a high-resolution textured 3D shape through geometry detailization and conditional texture generation applied to an input coarse voxel shape. Trained on a…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Qimin Chen , Zhiqin Chen , Hang Zhou , Hao Zhang

We introduce a novel geometry-guided online video view synthesis method with enhanced view and temporal consistency. Traditional approaches achieve high-quality synthesis from dense multi-view camera setups but require significant…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Hyunho Ha , Lei Xiao , Christian Richardt , Thu Nguyen-Phuoc , Changil Kim , Min H. Kim , Douglas Lanman , Numair Khan

While text-to-3D and image-to-3D generation tasks have received considerable attention, one important but under-explored field between them is controllable text-to-3D generation, which we mainly focus on in this work. To address this task,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Zhiqi Li , Yiming Chen , Lingzhe Zhao , Peidong Liu

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun
‹ Prev 1 3 4 5 6 7 10 Next ›