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Related papers: Layout-your-3D: Controllable and Precise 3D Genera…

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Recently, generating 3D assets with the control of condition images has achieved impressive quality. However, existing 3D generation methods are limited to handling a single control objective and lack the ability to utilize multiple images…

Graphics · Computer Science 2026-02-20 Xuancheng Jin , Rengan Xie , Wenting Zheng , Rui Wang , Hujun Bao , Yuchi Huo

3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel deep-learning based approach for automatically generating…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Yongzhi Xu , Yonhon Ng , Yifu Wang , Inkyu Sa , Yunfei Duan , Zhenhong Sun , Yang Li , Pan Ji , Hongdong Li

We present Dual3D, a novel text-to-3D generation framework that generates high-quality 3D assets from texts in only $1$ minute.The key component is a dual-mode multi-view latent diffusion model. Given the noisy multi-view latents, the 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Xinyang Li , Zhangyu Lai , Linning Xu , Jianfei Guo , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

In recent years, there has been significant progress in 2D generative face models fueled by applications such as animation, synthetic data generation, and digital avatars. However, due to the absence of 3D information, these 2D models often…

Computer Vision and Pattern Recognition · Computer Science 2023-10-30 Aashish Rai , Hiresh Gupta , Ayush Pandey , Francisco Vicente Carrasco , Shingo Jason Takagi , Amaury Aubel , Daeil Kim , Aayush Prakash , Fernando de la Torre

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

3D human modeling has been widely used for engaging interaction in gaming, film, and animation. The customization of these characters is crucial for creativity and scalability, which highlights the importance of controllability. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Tsu-Jui Fu , Wenhan Xiong , Yixin Nie , Jingyu Liu , Barlas Oğuz , William Yang Wang

Text-to-image generation models have seen considerable advancement, catering to the increasing interest in personalized image creation. Current customization techniques often necessitate users to provide multiple images (typically 3-5) for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Linhao Zhong , Yan Hong , Wentao Chen , Binglin Zhou , Yiyi Zhang , Jianfu Zhang , Liqing Zhang

While generative artificial intelligence has advanced significantly across text, image, audio, and video domains, 3D generation remains comparatively underdeveloped due to fundamental challenges such as data scarcity, algorithmic…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Weiyu Li , Xuanyang Zhang , Zheng Sun , Di Qi , Hao Li , Wei Cheng , Weiwei Cai , Shihao Wu , Jiarui Liu , Zihao Wang , Xiao Chen , Feipeng Tian , Jianxiong Pan , Zeming Li , Gang Yu , Xiangyu Zhang , Daxin Jiang , Ping Tan

3D layout generation and editing play a crucial role in Embodied AI and immersive VR interaction. However, manual creation requires tedious labor, while data-driven generation often lacks diversity. The emergence of large models introduces…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Haiyan Jiang , Deyu Zhang , Dongdong Weng , Weitao Song , Henry Been-Lirn Duh

It is common in graphic design humans visually arrange various elements according to their design intent and semantics. For example, a title text almost always appears on top of other elements in a document. In this work, we generate…

Computer Vision and Pattern Recognition · Computer Science 2021-08-03 Kotaro Kikuchi , Edgar Simo-Serra , Mayu Otani , Kota Yamaguchi

As 3D generation techniques continue to flourish, the demand for generating personalized content is rapidly rising. Users increasingly seek to apply various editing methods to polish generated 3D content, aiming to enhance its color, style,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Weitao Wang , Haoran Xu , Jun Meng , Haoqian Wang

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

Controllable image generation has always been one of the core demands in image generation, aiming to create images that are both creative and logical while satisfying additional specified conditions. In the post-AIGC era, controllable…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Guandong Li

Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed. However, a challenge arises when the specific appearances need customizing at designated viewpoints but referring…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Junkai Yan , Yipeng Gao , Qize Yang , Xihan Wei , Xuansong Xie , Ancong Wu , Wei-Shi Zheng

In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical rendering pipeline can be replaced by efficient models that are…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Yiyi Liao , Katja Schwarz , Lars Mescheder , Andreas Geiger

Prompt-driven scene synthesis allows users to generate complete 3D environments from textual descriptions. Current text-to-scene methods often struggle with complex geometries and object transformations, and tend to show weak adherence to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Frédéric Berdoz , Luca A. Lanzendörfer , Nick Tuninga , Roger Wattenhofer

Text-to-3D generation is a valuable technology in virtual reality and digital content creation. While recent works have pushed the boundaries of text-to-3D generation, producing high-fidelity 3D objects with inefficient prompts and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Wenqing Wang , Yun Fu

Existing text-based 3D generation methods generate attractive results but lack detailed geometry control. Sketches, known for their conciseness and expressiveness, have contributed to intuitive 3D modeling but are confined to producing…

Graphics · Computer Science 2024-05-15 Feng-Lin Liu , Hongbo Fu , Yu-Kun Lai , Lin Gao

Generative AI has made rapid progress in text, image, and video synthesis, yet text-to-3D modeling for scientific design remains particularly challenging due to limited controllability and high computational cost. Most existing 3D…

Graphics · Computer Science 2026-04-01 Rachel K. Luu , Markus J. Buehler

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Hyojun Go , Byeongjun Park , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim