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Diffusion models trained on large-scale text-image datasets have demonstrated a strong capability of controllable high-quality image generation from arbitrary text prompts. However, the generation quality and generalization ability of 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Ying-Tian Liu , Yuan-Chen Guo , Guan Luo , Heyi Sun , Wei Yin , Song-Hai Zhang

Recent years have witnessed the strong power of large text-to-image diffusion models for the impressive generative capability to create high-fidelity images. However, it is very tricky to generate desired images using only text prompt as it…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Hu Ye , Jun Zhang , Sibo Liu , Xiao Han , Wei Yang

We introduce X-Ray, a novel 3D sequential representation inspired by the penetrability of x-ray scans. X-Ray transforms a 3D object into a series of surface frames at different layers, making it suitable for generating 3D models from…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Tao Hu , Wenhang Ge , Yuyang Zhao , Gim Hee Lee

We present I2V3D, a novel framework for animating static images into dynamic videos with precise 3D control, leveraging the strengths of both 3D geometry guidance and advanced generative models. Our approach combines the precision of a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Zhiyuan Zhang , Dongdong Chen , Jing Liao

We present BlenderFusion, a generative visual compositing framework that synthesizes new scenes by recomposing objects, camera, and background. It follows a layering-editing-compositing pipeline: (i) segmenting and converting visual inputs…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiacheng Chen , Ramin Mehran , Xuhui Jia , Saining Xie , Sanghyun Woo

The ability to generate highly realistic 2D images from mere text prompts has recently made huge progress in terms of speed and quality, thanks to the advent of image diffusion models. Naturally, the question arises if this can be also…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Christina Tsalicoglou , Fabian Manhardt , Alessio Tonioni , Michael Niemeyer , Federico Tombari

Transformer based methods have enabled users to create, modify, and comprehend text and image data. Recently proposed Large Reconstruction Models (LRMs) further extend this by providing the ability to generate high-quality 3D models with…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Kunal Kathare , Ankit Dhiman , K Vikas Gowda , Siddharth Aravindan , Shubham Monga , Basavaraja Shanthappa Vandrotti , Lokesh R Boregowda

Recently, the field of text-guided 3D scene generation has garnered significant attention. High-quality generation that aligns with physical realism and high controllability is crucial for practical 3D scene applications. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yang Zhou , Zongjin He , Qixuan Li , Chao Wang

Recent text-to-3D generation methods achieve impressive 3D content creation capacity thanks to the advances in image diffusion models and optimizing strategies. However, current methods struggle to generate correct 3D content for a complex…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Xinhua Cheng , Tianyu Yang , Jianan Wang , Yu Li , Lei Zhang , Jian Zhang , Li Yuan

Image-conditioned generation methods, such as depth- and canny-conditioned approaches, have demonstrated remarkable abilities for precise image synthesis. However, existing models still struggle to accurately control the content of multiple…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Dewei Zhou , Mingwei Li , Zongxin Yang , Yi Yang

Controllable 3D scene generation has extensive applications in virtual reality and interior design, where the generated scenes should exhibit high levels of realism and controllability in terms of geometry. Scene graphs provide a suitable…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Zhifei Yang , Keyang Lu , Chao Zhang , Jiaxing Qi , Hanqi Jiang , Ruifei Ma , Shenglin Yin , Yifan Xu , Mingzhe Xing , Zhen Xiao , Jieyi Long , Guangyao Zhai

Text-to-3D generation has recently seen significant progress. To enhance its practicality in real-world applications, it is crucial to generate multiple independent objects with interactions, similar to layer-compositing in 2D image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Zizheng Yan , Jiapeng Zhou , Fanpeng Meng , Yushuang Wu , Lingteng Qiu , Zisheng Ye , Shuguang Cui , Guanying Chen , Xiaoguang Han

Text-to-3D modelling has seen exciting progress by combining generative text-to-image models with image-to-3D methods like Neural Radiance Fields. DreamFusion recently achieved high-quality results but requires a lengthy, per-prompt…

Interactable objects are ubiquitous in our daily lives. Recent advances in 3D generative models make it possible to automate the modeling of these objects, benefiting a range of applications from 3D printing to the creation of robot…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Rundong Luo , Haoran Geng , Congyue Deng , Puhao Li , Zan Wang , Baoxiong Jia , Leonidas Guibas , Siyuan Huang

The generation of high-quality, animatable 3D head avatars from text has enormous potential in content creation applications such as games, movies, and embodied virtual assistants. Current text-to-3D generation methods typically combine…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Yiqian Wu , Malte Prinzler , Xiaogang Jin , Siyu Tang

Generating articulated objects, such as laptops and microwaves, is a crucial yet challenging task with extensive applications in Embodied AI and AR/VR. Current image-to-3D methods primarily focus on surface geometry and texture, neglecting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Ruijie Lu , Yu Liu , Jiaxiang Tang , Junfeng Ni , Yuxiang Wang , Diwen Wan , Gang Zeng , Yixin Chen , Siyuan Huang

Text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models has shown great promise but still suffers from inconsistent 3D geometric structures (Janus problems) and severe artifacts. The aforementioned problems…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Baorui Ma , Haoge Deng , Junsheng Zhou , Yu-Shen Liu , Tiejun Huang , Xinlong Wang

Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

Advancements in text-to-image diffusion models have led to significant progress in fast 3D content creation. One common approach is to generate a set of multi-view images of an object, and then reconstruct it into a 3D model. However, this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Yiftach Edelstein , Or Patashnik , Dana Cohen-Bar , Lihi Zelnik-Manor

While image diffusion models have made significant progress in text-driven 3D content creation, they often fail to accurately capture the intended meaning of text prompts, especially for view information. This limitation leads to the Janus…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Zhipeng Hu , Minda Zhao , Chaoyi Zhao , Xinyue Liang , Lincheng Li , Zeng Zhao , Changjie Fan , Xiaowei Zhou , Xin Yu
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