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Recent AI-based 3D content creation has largely evolved along two paths: feed-forward image-to-3D reconstruction approaches and 3D generative models trained with 2D or 3D supervision. In this work, we show that existing feed-forward…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Suttisak Wizadwongsa , Jinfan Zhou , Edward Li , Jeong Joon Park

We propose a training-free approach to 3D editing that enables the editing of a single shape within a few minutes. The edited 3D mesh aligns well with the prompts, and remains identical for regions that are not intended to be altered. To…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ziya Erkoç , Can Gümeli , Chaoyang Wang , Matthias Nießner , Angela Dai , Peter Wonka , Hsin-Ying Lee , Peiye Zhuang

We present DanceText, a training-free framework for multilingual text editing in images, designed to support complex geometric transformations and achieve seamless foreground-background integration. While diffusion-based generative models…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Zhenyu Yu , Mohd Yamani Idna Idris , Hua Wang , Pei Wang , Rizwan Qureshi , Shaina Raza , Aman Chadha , Yong Xiang , Zhixiang Chen

Recent advancements in zero-shot video diffusion models have shown promise for text-driven video editing, but challenges remain in achieving high temporal consistency. To address this, we introduce Video-3DGS, a 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Inkyu Shin , Qihang Yu , Xiaohui Shen , In So Kweon , Kuk-Jin Yoon , Liang-Chieh Chen

Recent breakthroughs in single-image 3D portrait reconstruction have enabled telepresence systems to stream 3D portrait videos from a single camera in real-time, democratizing telepresence. However, per-frame 3D reconstruction exhibits…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Shengze Wang , Xueting Li , Chao Liu , Matthew Chan , Michael Stengel , Henry Fuchs , Shalini De Mello , Koki Nagano

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

While diffusion models have demonstrated remarkable progress in 2D image generation and editing, extending these capabilities to 3D editing remains challenging, particularly in maintaining multi-view consistency. Classical approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yufeng Chi , Huimin Ma , Kafeng Wang , Jianmin Li

We present BlenderFusion, a generative visual compositing framework that synthesizes new scenes by recomposing objects, camera, and background. It follows a layering-editing-compositing pipeline: (i) segmenting and converting visual inputs…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiacheng Chen , Ramin Mehran , Xuhui Jia , Saining Xie , Sanghyun Woo

Feed-forward foundation models for multi-view 3-dimensional (3D) reconstruction have been trained on large-scale datasets of perspective images; when tested on wide field-of-view images, e.g., from a fisheye camera, their performance…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Ruxiao Duan , Erin Hong , Dongxu Zhao , Eric Turner , Alex Wong , Yunwen Zhou

Image-driven video editing aims to propagate edit contents from the modified first frame to the remaining frames. Existing methods usually invert the source video to noise using a pre-trained image-to-video (I2V) model and then guide the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Maomao Li , Yunfei Liu , Yu Li

3D editing has shown remarkable capability in editing scenes based on various instructions. However, existing methods struggle with achieving intuitive, localized editing, such as selectively making flowers blossom. Drag-style editing has…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Chenghao Gu , Zhenzhe Li , Zhengqi Zhang , Yunpeng Bai , Shuzhao Xie , Zhi Wang

We propose MLV-Edit, a training-free, flow-based framework that address the unique challenges of minute-level video editing. While existing techniques excel in short-form video manipulation, scaling them to long-duration videos remains…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Yangyi Cao , Yuanhang Li , Lan Chen , Qi Mao

Recent trends in sparse-view 3D reconstruction have taken two different paths: feed-forward reconstruction that predicts pixel-aligned point maps without a complete geometry, and generative 3D reconstruction that generates complete geometry…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Siyou Lin , Zhou Xue , Hongwen Zhang , Liang An , Dongping Li , Shaohui Jiao , Yebin Liu

Recent advances in vision-language models have facilitated progress in sketch generation. However, existing specialized methods primarily focus on generic synthesis and lack mechanisms for precise control over sketch styles. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Tengjie Li , Shikui Tu , Lei Xu

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimization. However, existing feedforward approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anran Wu , Long Peng , Xin Di , Xueyuan Dai , Chen Wu , Yang Wang , Xueyang Fu , Yang Cao , Zheng-Jun Zha

View-conditioned 3D generators such as SAM 3D, TRELLIS and Hunyuan3D produce high-quality object reconstructions from a single view, but real-world visual observation often arrives as long monocular streams. Naively applying these…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Kaichen Zhou , Zeyang Bai , Xinhai Chang , Mengyu Wang , Paul Liang , Fangneng Zhan

Text-driven 3D scene editing has recently attracted increasing attention. Most existing methods follow a render-edit-optimize pipeline, where multi-view images are rendered from a 3D scene, edited with 2D image editors, and then used to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Pufan Li , Bi'an Du , Shenghe Zheng , Junyi Yao , Wei Hu

Rectified Flow text-to-image models surpass diffusion models in image quality and text alignment, but adapting ReFlow for real-image editing remains challenging. We propose a new real-image editing method for ReFlow by analyzing the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Jimyeong Kim , Jungwon Park , Yeji Song , Nojun Kwak , Wonjong Rhee

Generating accurate 3D models is a challenging problem that traditionally requires explicit learning from 3D datasets using supervised learning. Although recent advances have shown promise in learning 3D models from 2D images, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Qijia Shen , Guangrun Wang

3D texture swapping allows for the customization of 3D object textures, enabling efficient and versatile visual transformations in 3D editing. While no dedicated method exists, adapted 2D editing and text-driven 3D editing approaches can…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Xiao Cao , Beibei Lin , Bo Wang , Zhiyong Huang , Robby T. Tan