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Related papers: SketchDream: Sketch-based Text-to-3D Generation an…

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The advancements in automatic text-to-3D generation have been remarkable. Most existing methods use pre-trained text-to-image diffusion models to optimize 3D representations like Neural Radiance Fields (NeRFs) via latent-space denoising…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Junzhe Zhu , Peiye Zhuang , Sanmi Koyejo

Text-guided image generation has progressed rapidly in recent years, inspiring major breakthroughs in text-guided shape generation. Recently, it has been shown that using score distillation, one can successfully text-guide a NeRF model to…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Gal Metzer , Elad Richardson , Or Patashnik , Raja Giryes , Daniel Cohen-Or

While text-to-3D and image-to-3D generation tasks have received considerable attention, one important but under-explored field between them is controllable text-to-3D generation, which we mainly focus on in this work. To address this task,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Zhiqi Li , Yiming Chen , Lingzhe Zhao , Peidong Liu

Deep learning-based sketch-to-clothing image generation provides the initial designs and inspiration in the fashion design processes. However, clothing generation from freehand drawing is challenging due to the sparse and ambiguous…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Yongming Zhang , Tianyu Zhang , Haoran Xie

Diffusion probabilistic models have demonstrated significant potential in generating high-quality, realistic medical images, providing a promising solution to the persistent challenge of data scarcity in the medical field. Nevertheless,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Delin An , Chaoli Wang

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

Sketch-based 3D reconstruction remains a challenging task due to the abstract and sparse nature of sketch inputs, which often lack sufficient semantic and geometric information. To address this, we propose Sketch2Symm, a two-stage…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Yan Zhou , Mingji Li , Xiantao Zeng , Jie Lin , Yuexia Zhou

Impressive progress in generative models and implicit representations gave rise to methods that can generate 3D shapes of high quality. However, being able to locally control and edit shapes is another essential property that can unlock…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Konstantinos Tertikas , Despoina Paschalidou , Boxiao Pan , Jeong Joon Park , Mikaela Angelina Uy , Ioannis Emiris , Yannis Avrithis , Leonidas Guibas

Sketch-based modeling strives to bring the ease and immediacy of drawing to the 3D world. However, while drawings are easy for humans to create, they are very challenging for computers to interpret due to their sparsity and ambiguity. We…

Graphics · Computer Science 2018-06-20 Johanna Delanoy , Mathieu Aubry , Phillip Isola , Alexei A. Efros , Adrien Bousseau

We present SENS, a novel method for generating and editing 3D models from hand-drawn sketches, including those of abstract nature. Our method allows users to quickly and easily sketch a shape, and then maps the sketch into the latent space…

Graphics · Computer Science 2024-02-22 Alexandre Binninger , Amir Hertz , Olga Sorkine-Hornung , Daniel Cohen-Or , Raja Giryes

We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively synthesize high…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Dave Zhenyu Chen , Yawar Siddiqui , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

We present a novel method for performing flexible, 3D-aware image content manipulation while enabling high-quality novel view synthesis. While NeRF-based approaches are effective for novel view synthesis, such models memorize the radiance…

Computer Vision and Pattern Recognition · Computer Science 2022-04-25 Verica Lazova , Vladimir Guzov , Kyle Olszewski , Sergey Tulyakov , Gerard Pons-Moll

We introduce a novel sketch-to-image tool that aligns with the iterative refinement process of artists. Our tool lets users sketch blocking strokes to coarsely represent the placement and form of objects and detail strokes to refine their…

Graphics · Computer Science 2024-10-28 Vishnu Sarukkai , Lu Yuan , Mia Tang , Maneesh Agrawala , Kayvon Fatahalian

We propose NeRF-Insert, a NeRF editing framework that allows users to make high-quality local edits with a flexible level of control. Unlike previous work that relied on image-to-image models, we cast scene editing as an in-painting…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Benet Oriol Sabat , Alessandro Achille , Matthew Trager , Stefano Soatto

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

Sketching is inherently a sequential process, in which strokes are drawn in a meaningful order to explore and refine ideas. However, most generative models treat sketches as static images, overlooking the temporal structure that underlies…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Hui Ren , Yuval Alaluf , Omer Bar Tal , Alexander Schwing , Antonio Torralba , Yael Vinker

3D shape modeling is labor-intensive, time-consuming, and requires years of expertise. To facilitate 3D shape modeling, we propose a 3D shape generation network that takes a 3D VR sketch as a condition. We assume that sketches are created…

Computer Vision and Pattern Recognition · Computer Science 2024-01-11 Ling Luo , Pinaki Nath Chowdhury , Tao Xiang , Yi-Zhe Song , Yulia Gryaditskaya

This paper presents a novel approach to inpainting 3D regions of a scene, given masked multi-view images, by distilling a 2D diffusion model into a learned 3D scene representation (e.g. a NeRF). Unlike 3D generative methods that explicitly…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Kira Prabhu , Jane Wu , Lynn Tsai , Peter Hedman , Dan B Goldman , Ben Poole , Michael Broxton

A plethora of text-guided image editing methods has recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models especially Stable Diffusion. Despite the success of diffusion models in…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Qihe Pan , Zhen Zhao , Zicheng Wang , Sifan Long , Yiming Wu , Wei Ji , Haoran Liang , Ronghua Liang

3D textured face reconstruction from sketches applicable in many scenarios such as animation, 3D avatars, artistic design, missing people search, etc., is a highly promising but underdeveloped research topic. On the one hand, the stylistic…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Zidu Wang , Xiangyu Zhu , Jiang Yu , Tianshuo Zhang , Zhen Lei
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