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Related papers: Sketch2NeRF: Multi-view Sketch-guided Text-to-3D G…

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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

Converting hand-drawn sketches into structured 3D geometries remains challenging due to the difficulty of representing non-Euclidean surfaces and maintaining topological consistency. Existing generative models such as GANs, NeRFs, and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Wenda Wang , Anqi Liu , Junqi Yang , Lei He , Luying Wang , Jiachen Lu , Weixin Huang

Recent methods in text-to-3D leverage powerful pretrained diffusion models to optimize NeRF. Notably, these methods are able to produce high-quality 3D scenes without training on 3D data. Due to the open-ended nature of the task, most…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Yuze He , Yushi Bai , Matthieu Lin , Wang Zhao , Yubin Hu , Jenny Sheng , Ran Yi , Juanzi Li , Yong-Jin Liu

We introduce InseRF, a novel method for generative object insertion in the NeRF reconstructions of 3D scenes. Based on a user-provided textual description and a 2D bounding box in a reference viewpoint, InseRF generates new objects in 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-01-11 Mohamad Shahbazi , Liesbeth Claessens , Michael Niemeyer , Edo Collins , Alessio Tonioni , Luc Van Gool , Federico Tombari

The creation of complex 3D scenes tailored to user specifications has been a tedious and challenging task with traditional 3D modeling tools. Although some pioneering methods have achieved automatic text-to-3D generation, they are generally…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Xiuyu Yang , Yunze Man , Jun-Kun Chen , Yu-Xiong Wang

Significant progress has recently been made in creative applications of large pre-trained models for downstream tasks in 3D vision, such as text-to-shape generation. This motivates our investigation of how these pre-trained models can be…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Aditya Sanghi , Pradeep Kumar Jayaraman , Arianna Rampini , Joseph Lambourne , Hooman Shayani , Evan Atherton , Saeid Asgari Taghanaki

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

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

2D concept art generation for 3D scenes is a crucial yet challenging task in computer graphics, as creating natural intuitive environments still demands extensive manual effort in concept design. While generative AI has simplified 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Zhenhong Sun , Yifu Wang , Yonhon Ng , Yongzhi Xu , Daoyi Dong , Hongdong Li , Pan Ji

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Recently, a surge of 3D style transfer methods has been proposed that leverage the scene reconstruction power of a pre-trained neural radiance field (NeRF). To successfully stylize a scene this way, one must first reconstruct a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Y. Wang , A. Gao , Y. Gong , Y. Zeng

We tackle the task of text-to-3D creation with pre-trained latent-based NeRFs (NeRFs that generate 3D objects given input latent code). Recent works such as DreamFusion and Magic3D have shown great success in generating 3D content using…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yu-Jhe Li , Tao Xu , Ji Hou , Bichen Wu , Xiaoliang Dai , Albert Pumarola , Peizhao Zhang , Peter Vajda , Kris Kitani

As a powerful representation of 3D scenes, the neural radiance field (NeRF) enables high-quality novel view synthesis from multi-view images. Stylizing NeRF, however, remains challenging, especially on simulating a text-guided style with…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Can Wang , Ruixiang Jiang , Menglei Chai , Mingming He , Dongdong Chen , Jing Liao

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

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

The neural radiance field (NeRF) achieved remarkable success in modeling 3D scenes and synthesizing high-fidelity novel views. However, existing NeRF-based methods focus more on the make full use of the image resolution to generate novel…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Yuqi Han , Tao Yu , Xiaohang Yu , Yuwang Wang , Qionghai Dai

2D-to-3D reconstruction is an ill-posed problem, yet humans are good at solving this problem due to their prior knowledge of the 3D world developed over years. Driven by this observation, we propose NeRDi, a single-view NeRF synthesis…

Computer Vision and Pattern Recognition · Computer Science 2022-12-08 Congyue Deng , Chiyu "Max'' Jiang , Charles R. Qi , Xinchen Yan , Yin Zhou , Leonidas Guibas , Dragomir Anguelov

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

Animation of 2D hand-drawn sketches provides an effective medium for visual communication. However, these sketches pose challenges, particularly in handling occlusions and accurately mapping motion. While 3D animation naturally addresses…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Gaurav Rai , Ojaswa Sharma