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

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Recent research has demonstrated that the combination of pretrained diffusion models with neural radiance fields (NeRFs) has emerged as a promising approach for text-to-3D generation. Simply coupling NeRF with diffusion models will result…

Computer Vision and Pattern Recognition · Computer Science 2023-06-19 Lu Yu , Wei Xiang , Kang Han

Creating 3D textured meshes using generative artificial intelligence has garnered significant attention recently. While existing methods support text-based generative texture generation or editing on 3D meshes, they often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Yudi Zhang , Qi Xu , Lei Zhang

Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, challenges remain in ensuring high-quality stylization and…

Graphics · Computer Science 2026-03-03 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

Recent remarkable improvements in large-scale text-to-image generative models have shown promising results in generating high-fidelity images. To further enhance editability and enable fine-grained generation, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Kangyeol Kim , Sunghyun Park , Junsoo Lee , Jaegul Choo

We introduce RealmDreamer, a technique for generating forward-facing 3D scenes from text descriptions. Our method optimizes a 3D Gaussian Splatting representation to match complex text prompts using pretrained diffusion models. Our key…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Jaidev Shriram , Alex Trevithick , Lingjie Liu , Ravi Ramamoorthi

In the field of sketch generation, raster-format trained models often produce non-stroke artifacts, while vector-format trained models typically lack a holistic understanding of sketches, leading to compromised recognizability. Moreover,…

Graphics · Computer Science 2025-11-19 Jin Zhou , Yi Zhou , Hongliang Yang , Pengfei Xu , Hui Huang

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

3D sketches are widely used for visually representing the 3D shape and structure of objects or scenes. However, the creation of 3D sketch often requires users to possess professional artistic skills. Existing research efforts primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yibo Zhang , Lihong Wang , Changqing Zou , Tieru Wu , Rui Ma

Text-driven 3D scene generation has seen significant advancements recently. However, most existing methods generate single-view images using generative models and then stitch them together in 3D space. This independent generation for each…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Wenrui Li , Fucheng Cai , Yapeng Mi , Zhe Yang , Wangmeng Zuo , Xingtao Wang , Xiaopeng Fan

Text driven diffusion models have shown remarkable capabilities in editing images. However, when editing 3D scenes, existing works mostly rely on training a NeRF for 3D editing. Recent NeRF editing methods leverages edit operations by…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Vivek Madhavaram , Shivangana Rawat , Chaitanya Devaguptapu , Charu Sharma , Manohar Kaul

The emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Green Rosh , Prateek Kukreja , Vishakha SR , Pawan Prasad B H

Advances in image diffusion models have recently led to notable improvements in the generation of high-quality images. In combination with Neural Radiance Fields (NeRFs), they enabled new opportunities in 3D generation. However, most…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Jan-Niklas Dihlmann , Andreas Engelhardt , Hendrik Lensch

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Recent advancements in 3D diffusion-based semantic scene generation have gained attention. However, existing methods rely on unconditional generation and require multiple resampling steps when editing scenes, which significantly limits…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Haowen Zheng , Yanyan Liang

We introduce "ImageDream," an innovative image-prompt, multi-view diffusion model for 3D object generation. ImageDream stands out for its ability to produce 3D models of higher quality compared to existing state-of-the-art,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Peng Wang , Yichun Shi

We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide vector sketch synthesis. In this paper, we introduce DiffSketcher, a novel algorithm for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Ximing Xing , Chuang Wang , Haitao Zhou , Jing Zhang , Qian Yu , Dong Xu

Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the back view) and inaccurate shapes (e.g., animals with extra…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Cheng Chen , Xiaofeng Yang , Fan Yang , Chengzeng Feng , Zhoujie Fu , Chuan-Sheng Foo , Guosheng Lin , Fayao 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

Creative sketch is a universal way of visual expression, but translating images from an abstract sketch is very challenging. Traditionally, creating a deep learning model for sketch-to-image synthesis needs to overcome the distorted input…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Qiang Wang , Di Kong , Fengyin Lin , Yonggang Qi

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