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Related papers: DragScene: Interactive 3D Scene Editing with Singl…

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Video generation models have shown their superior ability to generate photo-realistic video. However, how to accurately control (or edit) the video remains a formidable challenge. The main issues are: 1) how to perform direct and accurate…

Graphics · Computer Science 2024-07-23 Yufan Deng , Ruida Wang , Yuhao Zhang , Yu-Wing Tai , Chi-Keung Tang

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Kai He , Chin-Hsuan Wu , Igor Gilitschenski

User-friendly 3D object editing is a challenging task that has attracted significant attention recently. The limitations of direct 3D object editing without 2D prior knowledge have prompted increased attention towards utilizing 2D…

Graphics · Computer Science 2024-05-10 Sitian Shen , Jing Xu , Yuheng Yuan , Xingyi Yang , Qiuhong Shen , Xinchao Wang

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

Instruction-guided 3D editing is a rapidly emerging field with the potential to broaden access to 3D content creation. However, existing methods face critical limitations: optimization-based approaches are prohibitively slow, while…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Weiwei Cai , Shuangkang Fang , Weicai Ye , Xin Dong , Yunhan Yang , Xuanyang Zhang , Wei Cheng , Yanpei Cao , Gang Yu , Tao Chen

We consider the problem of editing 3D objects and scenes based on open-ended language instructions. A common approach to this problem is to use a 2D image generator or editor to guide the 3D editing process, obviating the need for 3D data.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Minghao Chen , Iro Laina , Andrea Vedaldi

Recent advancements in 3D scene editing have been propelled by the rapid development of generative models. Existing methods typically utilize generative models to perform text-guided editing on 3D representations, such as 3D Gaussian…

Graphics · Computer Science 2025-05-27 Yansong Qu , Dian Chen , Xinyang Li , Xiaofan Li , Shengchuan Zhang , Liujuan Cao , Rongrong Ji

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

Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qihang Zhang , Yinghao Xu , Chaoyang Wang , Hsin-Ying Lee , Gordon Wetzstein , Bolei Zhou , Ceyuan Yang

DragDiffusion is a diffusion-based method for interactive point-based image editing that enables users to manipulate images by directly dragging selected points. The method claims that accurate spatial control can be achieved by optimizing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Ali Subhan , Ashir Raza

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

The transformative potential of 3D content creation has been progressively unlocked through advancements in generative models. Recently, intuitive drag editing with geometric changes has attracted significant attention in 2D editing yet…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Jiahua Dong , Yu-Xiong Wang

Generative models have achieved significant progress in advancing 2D image editing, demonstrating exceptional precision and realism. However, they often struggle with consistency and object identity preservation due to their inherent…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yuhuan Xie , Aoxuan Pan , Ming-Xian Lin , Wei Huang , Yi-Hua Huang , Xiaojuan Qi

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

Real-time, high-fidelity reconstruction of dynamic driving scenes is challenged by complex dynamics and sparse views, with prior methods struggling to balance quality and efficiency. We propose DrivingScene, an online, feed-forward…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Qirui Hou , Wenzhang Sun , Chang Zeng , Chunfeng Wang , Hao Li , Jianxun Cui

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

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai 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

Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regularization or feed-forward deterministic model) to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hanyang Wang , Fangfu Liu , Jiawei Chi , Yueqi Duan

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim
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