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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

Despite recent advances in large-scale text-to-image generative models, manipulating real images with these models remains a challenging problem. The main limitations of existing editing methods are that they either fail to perform with…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Vadim Titov , Madina Khalmatova , Alexandra Ivanova , Dmitry Vetrov , Aibek Alanov

Text-guided 3D editing aims to modify existing 3D assets using natural-language instructions. Current methods struggle to jointly understand complex prompts, automatically localize edits in 3D, and preserve unedited content. We introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Yankuan Chi , Xiang Li , Zixuan Huang , James M. Rehg

This paper presents UltraEdit, a large-scale (approximately 4 million editing samples), automatically generated dataset for instruction-based image editing. Our key idea is to address the drawbacks in existing image editing datasets like…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Haozhe Zhao , Xiaojian Ma , Liang Chen , Shuzheng Si , Rujie Wu , Kaikai An , Peiyu Yu , Minjia Zhang , Qing Li , Baobao Chang

The creation of 3D scenes has traditionally been both labor-intensive and costly, requiring designers to meticulously configure 3D assets and environments. Recent advancements in generative AI, including text-to-3D and image-to-3D methods,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Ziyang Yan , Yihua Shao , Minwen Liao , Siyu Chen , Nan Wang , Muyuan Lin , Jenq-Neng Hwang , Hao Zhao , Fabio Remondino , Lei Li

Implicit surface representations are valued for their compactness and continuity, but they pose significant challenges for editing. Despite recent advancements, existing methods often fail to preserve identity and maintain geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Nail Ibrahimli , Julian F. P. Kooij , Liangliang Nan

Reconstructing 3D objects from extremely sparse views is a long-standing and challenging problem. While recent techniques employ image diffusion models for generating plausible images at novel viewpoints or for distilling pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zi-Xin Zou , Weihao Cheng , Yan-Pei Cao , Shi-Sheng Huang , Ying Shan , Song-Hai Zhang

We propose ClipFace, a novel self-supervised approach for text-guided editing of textured 3D morphable model of faces. Specifically, we employ user-friendly language prompts to enable control of the expressions as well as appearance of 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Shivangi Aneja , Justus Thies , Angela Dai , Matthias Nießner

Text-guided image and 3D editing have advanced with diffusion-based models, yet methods like Delta Denoising Score often struggle with stability, spatial control, and editing strength. These limitations stem from reliance on complex…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Haiming Zhu , Yangyang Xu , Chenshu Xu , Tingrui Shen , Wenxi Liu , Yong Du , Jun Yu , Shengfeng He

Recent advances in foundation models have driven remarkable progress in image editing, yet their extension to 3D editing remains underexplored. A natural approach is to replace the image editing modules in existing workflows with foundation…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Huaizhi Qu , Ruichen Zhang , Shuqing Luo , Luchao Qi , Zhihao Zhang , Xiaoming Liu , Roni Sengupta , Tianlong Chen

While text-3D editing has made significant strides in leveraging score distillation sampling, emerging approaches still fall short in delivering separable, precise and consistent outcomes that are vital to content creation. In response, we…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yuhan Li , Yishun Dou , Yue Shi , Yu Lei , Xuanhong Chen , Yi Zhang , Peng Zhou , Bingbing Ni

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

Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details. To…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yixin Chen , Junfeng Ni , Nan Jiang , Yaowei Zhang , Yixin Zhu , Siyuan Huang

Recent advances in deep generative modeling have unlocked unprecedented opportunities for video synthesis. In real-world applications, however, users often seek tools to faithfully realize their creative editing intentions with precise and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yuhao Liu , Tengfei Wang , Fang Liu , Zhenwei Wang , Rynson W. H. Lau

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

Many 3D scene editing tasks focus on modifying local regions rather than the entire scene, except for some global applications like style transfer, and in the context of 3D Gaussian Splatting (3DGS), where scenes are represented by a series…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Lanqing Guo , Yufei Wang , Hezhen Hu , Yan Zheng , Yeying Jin , Siyu Huang , Zhangyang Wang

There has recently been great interest in neural rendering methods. Some approaches use 3D geometry reconstructed with Multi-View Stereo (MVS) but cannot recover from the errors of this process, while others directly learn a volumetric…

Computer Vision and Pattern Recognition · Computer Science 2021-09-09 Georgios Kopanas , Julien Philip , Thomas Leimkühler , George Drettakis

Drag-based editing allows precise object manipulation through point-based control, offering user convenience. However, current methods often suffer from a geometric inconsistency problem by focusing exclusively on matching user-defined…

Graphics · Computer Science 2025-07-14 Gwanhyeong Koo , Sunjae Yoon , Younghwan Lee , Ji Woo Hong , Chang D. Yoo

Current text-driven image editing methods typically follow one of two directions: relying on large-scale, high-quality editing pair datasets to improve editing precision and diversity, or exploring alternative dataset-free techniques.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Chenrui Ma , Xi Xiao , Tianyang Wang , Yanning Shen

The availability of high-speed 3D video sensors has greatly facilitated 3D shape acquisition of dynamic and deformable objects, but high frame rate 3D reconstruction is always degraded by spatial noise and temporal fluctuations. This paper…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Jie Zhang , Christos Maniatis , Luis Horna , Robert B. Fisher