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Related papers: SKED: Sketch-guided Text-based 3D Editing

200 papers

We propose a method for scene-level sketch-to-photo synthesis with text guidance. Although object-level sketch-to-photo synthesis has been widely studied, whole-scene synthesis is still challenging without reference photos that adequately…

Computer Vision and Pattern Recognition · Computer Science 2023-02-15 AprilPyone MaungMaung , Makoto Shing , Kentaro Mitsui , Kei Sawada , Fumio Okura

Generating realistic 3D scenes is challenging due to the complexity of room layouts and object geometries.We propose a sketch based knowledge enhanced diffusion architecture (SEK) for generating customized, diverse, and plausible 3D scenes.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Zijie Wu , Mingtao Feng , Yaonan Wang , He Xie , Weisheng Dong , Bo Miao , Ajmal Mian

A neural radiance field (NeRF) is a scene model supporting high-quality view synthesis, optimized per scene. In this paper, we explore enabling user editing of a category-level NeRF - also known as a conditional radiance field - trained on…

Computer Vision and Pattern Recognition · Computer Science 2021-06-07 Steven Liu , Xiuming Zhang , Zhoutong Zhang , Richard Zhang , Jun-Yan Zhu , Bryan Russell

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

By lifting the pre-trained 2D diffusion models into Neural Radiance Fields (NeRFs), text-to-3D generation methods have made great progress. Many state-of-the-art approaches usually apply score distillation sampling (SDS) to optimize the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Yuze He , Yushi Bai , Matthieu Lin , Jenny Sheng , Yubin Hu , Qi Wang , Yu-Hui Wen , Yong-Jin Liu

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

In this paper, we present TEXTure, a novel method for text-guided generation, editing, and transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model, TEXTure applies an iterative scheme that paints a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Elad Richardson , Gal Metzer , Yuval Alaluf , Raja Giryes , Daniel Cohen-Or

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

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

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

Diffusion-based text-to-image models ignited immense attention from the vision community, artists, and content creators. Broad adoption of these models is due to significant improvement in the quality of generations and efficient…

Computer Vision and Pattern Recognition · Computer Science 2023-10-19 Tianfu Wang , Menelaos Kanakis , Konrad Schindler , Luc Van Gool , Anton Obukhov

Neural Radiance Fields (NeRFs) have emerged as a popular approach for novel view synthesis. While NeRFs are quickly being adapted for a wider set of applications, intuitively editing NeRF scenes is still an open challenge. One important…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Ashkan Mirzaei , Tristan Aumentado-Armstrong , Konstantinos G. Derpanis , Jonathan Kelly , Marcus A. Brubaker , Igor Gilitschenski , Alex Levinshtein

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

Recent advances in diffusion models such as ControlNet have enabled geometrically controllable, high-fidelity text-to-image generation. However, none of them addresses the question of adding such controllability to text-to-3D generation. In…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Sungwon Hwang , Junha Hyung , Jaegul Choo

Recent CLIP-guided 3D optimization methods, such as DreamFields and PureCLIPNeRF, have achieved impressive results in zero-shot text-to-3D synthesis. However, due to scratch training and random initialization without prior knowledge, these…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Jiale Xu , Xintao Wang , Weihao Cheng , Yan-Pei Cao , Ying Shan , Xiaohu Qie , Shenghua Gao

NeRF's high-quality scene synthesis capability was quickly accepted by scholars in the years after it was proposed, and significant progress has been made in 3D scene representation and synthesis. However, the high computational cost limits…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Shun Fang , Ming Cui , Xing Feng , Yanan Zhang

Distilling 3D representations from pretrained 2D diffusion models is essential for 3D creative applications across gaming, film, and interior design. Current SDS-based methods are hindered by inefficient information distillation from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Haoran Li , Yuli Tian , Yonghui Wang , Yong Liao , Lin Wang , Yuyang Wang , Peng Yuan Zhou

Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However, most existing works focus solely on the direct generation, ignoring the editing, restricting them from synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Yunjie Wu , Yapeng Meng , Zhipeng Hu , Lincheng Li , Haoqian Wu , Kun Zhou , Weiwei Xu , Xin Yu

Image and shape editing are ubiquitous among digital artworks. Graphics algorithms facilitate artists and designers to achieve desired editing intents without going through manually tedious retouching. In the recent advance of machine…

Graphics · Computer Science 2023-04-20 Cheng-Kang Ted Chao , Yotam Gingold

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