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Deep generative approaches have recently made considerable progress in image inpainting by introducing structure priors. Due to the lack of proper interaction with image texture during structure reconstruction, however, current solutions…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Xiefan Guo , Hongyu Yang , Di Huang

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

The modern computer graphics pipeline can synthesize images at remarkable visual quality; however, it requires well-defined, high-quality 3D content as input. In this work, we explore the use of imperfect 3D content, for instance, obtained…

Computer Vision and Pattern Recognition · Computer Science 2019-04-30 Justus Thies , Michael Zollhöfer , Matthias Nießner

Recent advancements in camera-trajectory-guided image-to-video generation offer higher precision and better support for complex camera control compared to text-based approaches. However, they also introduce significant usability challenges,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Teng Li , Guangcong Zheng , Rui Jiang , Shuigen Zhan , Tao Wu , Yehao Lu , Yining Lin , Chuanyun Deng , Yepan Xiong , Min Chen , Lin Cheng , Xi Li

Generating realistic 3D objects from single-view images requires natural appearance, 3D consistency, and the ability to capture multiple plausible interpretations of unseen regions. Existing approaches often rely on fine-tuning pretrained…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Pufan Li , Bi'an Du , Wei Hu

This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or generation from procedural models. Generating textures from…

Computer Vision and Pattern Recognition · Computer Science 2017-03-30 Yanhai Gan , Huifang Chi , Ying Gao , Jun Liu , Guoqiang Zhong , Junyu Dong

The field of advanced text-to-image generation is witnessing the emergence of unified frameworks that integrate powerful text encoders, such as CLIP and T5, with Diffusion Transformer backbones. Although there have been efforts to control…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Liang Chen , Shuai Bai , Wenhao Chai , Weichu Xie , Haozhe Zhao , Leon Vinci , Junyang Lin , Baobao Chang

We are witnessing a proliferation of textured 3D models captured from the real world with automatic photo-reconstruction tools. Digital 3D models of this class come with a unique set of characteristics and defects -- especially concerning…

Graphics · Computer Science 2020-12-29 Andrea Maggiordomo , Federico Ponchio , Paolo Cignoni , Marco Tarini

Novel photo-realistic texture synthesis is an important task for generating novel scenes, including asset generation for 3D simulations. However, to date, these methods predominantly generate textured objects in 2D space. If we rely on 2D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-09 Dharma KC , Clayton T. Morrison , Bradley Walls

Recent diffusion-based Single-image 3D portrait generation methods typically employ 2D diffusion models to provide multi-view knowledge, which is then distilled into 3D representations. However, these methods usually struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Haoran Wei , Wencheng Han , Xingping Dong , Jianbing Shen

DreamFusion established a new paradigm for unsupervised 3D reconstruction from virtual views by combining advances in generative models and differentiable rendering. However, the underlying multi-view rendering, along with supervision from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Ananta R. Bhattarai , Xingzhe He , Alla Sheffer , Helge Rhodin

Image inpainting techniques have shown significant improvements by using deep neural networks recently. However, most of them may either fail to reconstruct reasonable structures or restore fine-grained textures. In order to solve this…

Computer Vision and Pattern Recognition · Computer Science 2019-08-13 Yurui Ren , Xiaoming Yu , Ruonan Zhang , Thomas H. Li , Shan Liu , Ge Li

Inpainting focuses on filling missing or corrupted regions of an image to blend seamlessly with its surrounding content and style. While conditional diffusion models have proven effective for text-guided inpainting, we introduce the novel…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Nicola Fanelli , Gennaro Vessio , Giovanna Castellano

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

We introduce a two-stream model for dynamic texture synthesis. Our model is based on pre-trained convolutional networks (ConvNets) that target two independent tasks: (i) object recognition, and (ii) optical flow prediction. Given an input…

Computer Vision and Pattern Recognition · Computer Science 2018-04-16 Matthew Tesfaldet , Marcus A. Brubaker , Konstantinos G. Derpanis

Facial images have extensive practical applications. Although the current large-scale text-image diffusion models exhibit strong generation capabilities, it is challenging to generate the desired facial images using only text prompt. Image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Dawei Dai , Mingming Jia , Yinxiu Zhou , Hang Xing , Chenghang Li

Mobile robots operating indoors must be prepared to navigate challenging scenes that contain transparent surfaces. This paper proposes a novel method for the fusion of acoustic and visual sensing modalities through implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Advaith V. Sethuraman , Onur Bagoren , Harikrishnan Seetharaman , Dalton Richardson , Joseph Taylor , Katherine A. Skinner

Text-driven 3D editing enables user-friendly 3D object or scene editing with text instructions. Due to the lack of multi-view consistency priors, existing methods typically resort to employing 2D generation or editing models to process each…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Liyi Chen , Ruihuang Li , Guowen Zhang , Pengfei Wang , Lei Zhang

The growing demand for high-fidelity video generation from textual descriptions has catalyzed significant research in this field. In this work, we introduce MagicVideo-V2 that integrates the text-to-image model, video motion generator,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-10 Weimin Wang , Jiawei Liu , Zhijie Lin , Jiangqiao Yan , Shuo Chen , Chetwin Low , Tuyen Hoang , Jie Wu , Jun Hao Liew , Hanshu Yan , Daquan Zhou , Jiashi Feng

We present a novel method for 3D surface reconstruction from multiple images where only a part of the object of interest is captured. Our approach builds on two recent developments: surface reconstruction using neural radiance fields for…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Savva Ignatyev , Daniil Selikhanovych , Oleg Voynov , Yiqun Wang , Peter Wonka , Stamatios Lefkimmiatis , Evgeny Burnaev