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Related papers: SENS: Part-Aware Sketch-based Implicit Neural Shap…

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A non-parametric interpretable texture synthesis method, called the NITES method, is proposed in this work. Although automatic synthesis of visually pleasant texture can be achieved by deep neural networks nowadays, the associated…

Computer Vision and Pattern Recognition · Computer Science 2020-09-04 Xuejing Lei , Ganning Zhao , C. -C. Jay Kuo

Sketch editing requires jointly handling high-level semantic changes and precise local redrawing, a combination that is particularly challenging for sparse, style-sensitive line art. Unlike natural images, sketches rely on minimal visual…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Han Zou , Yan Zhang , Ruiqi Yu , Cong Xie , Jie Huang , Zhenpeng Zhan

The goal of this paper is to learn dense 3D shape correspondence for topology-varying objects in an unsupervised manner. Conventional implicit functions estimate the occupancy of a 3D point given a shape latent code. Instead, our novel…

Computer Vision and Pattern Recognition · Computer Science 2020-10-27 Feng Liu , Xiaoming Liu

This paper introduces a method for learning to generate line drawings from 3D models. Our architecture incorporates a differentiable module operating on geometric features of the 3D model, and an image-based module operating on view-based…

Computer Vision and Pattern Recognition · Computer Science 2020-04-07 Difan Liu , Mohamed Nabail , Aaron Hertzmann , Evangelos Kalogerakis

Most deep learning approaches to comprehensive semantic modeling of 3D indoor spaces require costly dense annotations in the 3D domain. In this work, we explore a central 3D scene modeling task, namely, semantic scene reconstruction without…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Junwen Huang , Alexey Artemov , Yujin Chen , Shuaifeng Zhi , Kai Xu , Matthias Nießner

In this paper, we study the problem of multi-view sketch correspondence, where we take as input multiple freehand sketches with different views of the same object and predict as output the semantic correspondence among the sketches. This…

Computer Vision and Pattern Recognition · Computer Science 2020-08-12 Deng Yu , Lei Li , Youyi Zheng , Manfred Lau , Yi-Zhe Song , Chiew-Lan Tai , Hongbo Fu

We present MS2Mesh-XR, a novel multi-modal sketch-to-mesh generation pipeline that enables users to create realistic 3D objects in extended reality (XR) environments using hand-drawn sketches assisted by voice inputs. In specific, users can…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yuqi Tong , Yue Qiu , Ruiyang Li , Shi Qiu , Pheng-Ann Heng

The study of neural generative models of human sketches is a fascinating contemporary modeling problem due to the links between sketch image generation and the human drawing process. The landmark SketchRNN provided breakthrough by…

Computer Vision and Pattern Recognition · Computer Science 2020-07-15 Ayan Das , Yongxin Yang , Timothy Hospedales , Tao Xiang , Yi-Zhe Song

Face sketch synthesis has made significant progress with the development of deep neural networks in these years. The delicate depiction of sketch portraits facilitates a wide range of applications like digital entertainment and law…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Xingqun Qi , Muyi Sun , Weining Wang , Xiaoxiao Dong , Qi Li , Caifeng Shan

Conceptualizing away the sketch processing details in a user interface will enable general users and domain experts to create more complex sketches. There are many domains for which sketch recognition systems are being developed. But they…

Computer Vision and Pattern Recognition · Computer Science 2012-11-13 Vasudha Vashisht , Tanupriya Choudhury , T. V. Prasad

Shape generation is the practice of producing 3D shapes as various representations for 3D content creation. Previous studies on 3D shape generation have focused on shape quality and structure, without or less considering the importance of…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Ruowei Wang , Yu Liu , Pei Su , Jianwei Zhang , Qijun Zhao

Sketch and speech are intuitive interaction methods that convey complementary information and have been independently used for 3D model retrieval in virtual environments. While sketch has been shown to be an effective retrieval method, not…

Human-Computer Interaction · Computer Science 2021-05-06 Daniele Giunchi , Alejandro Sztrajman , Stuart James , Anthony Steed

Recent advancements in large vision-language models have enabled highly expressive and diverse vector sketch generation. However, state-of-the-art methods rely on a time-consuming optimization process involving repeated feedback from a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Ellie Arar , Yarden Frenkel , Daniel Cohen-Or , Ariel Shamir , Yael Vinker

Given an abstract, deformed, ordinary sketch from untrained amateurs like you and me, this paper turns it into a photorealistic image - just like those shown in Fig. 1(a), all non-cherry-picked. We differ significantly from prior art in…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Subhadeep Koley , Ayan Kumar Bhunia , Aneeshan Sain , Pinaki Nath Chowdhury , Tao Xiang , Yi-Zhe Song

Recent progress in human shape learning, shows that neural implicit models are effective in generating 3D human surfaces from limited number of views, and even from a single RGB image. However, existing monocular approaches still struggle…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Marco Pesavento , Yuanlu Xu , Nikolaos Sarafianos , Robert Maier , Ziyan Wang , Chun-Han Yao , Marco Volino , Edmond Boyer , Adrian Hilton , Tony Tung

Neural shape models can represent complex 3D shapes with a compact latent space. When applied to dynamically deforming shapes such as the human hands, however, they would need to preserve temporal coherence of the deformation as well as the…

Computer Vision and Pattern Recognition · Computer Science 2021-10-06 Binbin Xu , Lingni Ma , Yuting Ye , Tanner Schmidt , Christopher D. Twigg , Steven Lovegrove

This paper presents a real-time generative drawing system that interprets and integrates both formal intent - the structural, compositional, and stylistic attributes of a sketch - and contextual intent - the semantic and thematic meaning…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Jookyung Song , Mookyoung Kang , Nojun Kwak

We present a generative model to synthesize 3D shapes as sets of handles -- lightweight proxies that approximate the original 3D shape -- for applications in interactive editing, shape parsing, and building compact 3D representations. Our…

Computer Vision and Pattern Recognition · Computer Science 2020-04-08 Matheus Gadelha , Giorgio Gori , Duygu Ceylan , Radomir Mech , Nathan Carr , Tamy Boubekeur , Rui Wang , Subhransu Maji

Many surface cues support three-dimensional shape perception, but people can sometimes still see shape when these features are missing -- in extreme cases, even when an object is completely occluded, as when covered with a draped cloth. We…

Neurons and Cognition · Quantitative Biology 2023-01-11 Ilker Yildirim , Max H. Siegel , Amir A. Soltani , Shraman Ray Chaudhari , Joshua B. Tenenbaum

Humans are able to precisely communicate diverse concepts by employing sketches, a highly reduced and abstract shape based representation of visual content. We propose, for the first time, a fully convolutional end-to-end architecture that…

Computer Vision and Pattern Recognition · Computer Science 2020-03-17 Moritz Kampelmühler , Axel Pinz
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