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We are witnessing significant breakthroughs in the technology for generating 3D objects from text. Existing approaches either leverage large text-to-image models to optimize a 3D representation or train 3D generators on object-centric…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Qihang Zhang , Chaoyang Wang , Aliaksandr Siarohin , Peiye Zhuang , Yinghao Xu , Ceyuan Yang , Dahua Lin , Bolei Zhou , Sergey Tulyakov , Hsin-Ying Lee

Procedural material graphs are a compact, parameteric, and resolution-independent representation that are a popular choice for material authoring. However, designing procedural materials requires significant expertise and publicly…

Graphics · Computer Science 2022-08-16 Paul Guerrero , Miloš Hašan , Kalyan Sunkavalli , Radomír Měch , Tamy Boubekeur , Niloy J. Mitra

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

Text-to-image diffusion models have demonstrated an impressive ability to produce high-quality outputs. However, they often struggle to accurately follow fine-grained spatial information in an input text. To this end, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Ran Galun , Sagie Benaim

Recent breakthroughs in Vision-Language (V&L) joint research have achieved remarkable results in various text-driven tasks. High-quality Text-to-video (T2V), a task that has been long considered mission-impossible, was proven feasible with…

Artificial Intelligence · Computer Science 2022-11-28 Yuxing Qiu , Feng Gao , Minchen Li , Govind Thattai , Yin Yang , Chenfanfu Jiang

In this paper, we propose Text2Scene, a model that generates various forms of compositional scene representations from natural language descriptions. Unlike recent works, our method does NOT use Generative Adversarial Networks (GANs).…

Computer Vision and Pattern Recognition · Computer Science 2019-06-11 Fuwen Tan , Song Feng , Vicente Ordonez

Text-to-motion generation has gained increasing attention, but most existing methods are limited to generating short-term motions that correspond to a single sentence describing a single action. However, when a text stream describes a…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Zhao Yang , Bing Su , Ji-Rong Wen

Painting is one of the ways for people to express their ideas, but what if people with disabilities in hands want to paint? To tackle this challenge, we create an end-to-end solution that can generate artistic images from text descriptions.…

Computer Vision and Pattern Recognition · Computer Science 2022-05-06 Qinghe Tian , Jean-Claude Franchitti

Meshes are commonly used as 3D maps since they encode the topology of the scene while being lightweight. Unfortunately, 3D meshes are mathematically difficult to handle directly because of their combinatorial and discrete nature. Therefore,…

Computer Vision and Pattern Recognition · Computer Science 2021-08-09 Antoni Rosinol , Luca Carlone

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Recent work has demonstrated that volumetric scene representations combined with differentiable volume rendering can enable photo-realistic rendering for challenging scenes that mesh reconstruction fails on. However, these methods entangle…

Computer Vision and Pattern Recognition · Computer Science 2021-03-02 Fanbo Xiang , Zexiang Xu , Miloš Hašan , Yannick Hold-Geoffroy , Kalyan Sunkavalli , Hao Su

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

Mesh models are a promising approach for encoding the structure of 3D objects. Current mesh reconstruction systems predict uniformly distributed vertex locations of a predetermined graph through a series of graph convolutions, leading to…

Computer Vision and Pattern Recognition · Computer Science 2019-02-01 Edward J. Smith , Scott Fujimoto , Adriana Romero , David Meger

In the realm of 3D computer vision, parametric models have emerged as a ground-breaking methodology for the creation of realistic and expressive 3D avatars. Traditionally, they rely on Principal Component Analysis (PCA), given its ability…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Rolandos Alexandros Potamias , Michail Tarasiou , Stylianos Ploumpis , Stefanos Zafeiriou

In recent years, substantial progress has been achieved in learning-based reconstruction of 3D objects. At the same time, generative models were proposed that can generate highly realistic images. However, despite this success in these…

Computer Vision and Pattern Recognition · Computer Science 2019-05-20 Michael Oechsle , Lars Mescheder , Michael Niemeyer , Thilo Strauss , Andreas Geiger

Deep learning based 3D shape generation methods generally utilize latent features extracted from color images to encode the semantics of objects and guide the shape generation process. These color image semantics only implicitly encode 3D…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 Rakesh Shrestha , Zhiwen Fan , Qingkun Su , Zuozhuo Dai , Siyu Zhu , Ping Tan

High-quality textures are critical for realistic 3D content creation, yet existing generative methods are slow, rely on UV maps, and often fail to remain faithful to a reference image. To address these challenges, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Arianna Rampini , Kanika Madan , Bruno Roy , AmirHossein Zamani , Derek Cheung

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

3D content creation via text-driven stylization has played a fundamental challenge to multimedia and graphics community. Recent advances of cross-modal foundation models (e.g., CLIP) have made this problem feasible. Those approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Tao Mei

Text-driven 3D scene generation techniques have made rapid progress in recent years. Their success is mainly attributed to using existing generative models to iteratively perform image warping and inpainting to generate 3D scenes. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Frank Zhang , Yibo Zhang , Quan Zheng , Rui Ma , Wei Hua , Hujun Bao , Weiwei Xu , Changqing Zou