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Diffusion-based point editing methods have gained significant traction in image editing tasks due to their ability to manipulate image semantics and fine details by applying localized perturbations on the manifold of noise latent. However,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Haoyang Hu , Masataka Seo , Yen-Wei Chen

Text-driven video editing aims to modify video content based on natural language instructions. While recent training-free methods have leveraged pretrained diffusion models, they often rely on an inversion-editing paradigm. This paradigm…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Guangzhao Li , Yanming Yang , Chenxi Song , Chi Zhang

Despite recent advances, diffusion-based text-to-image models still struggle with accurate text rendering. Several studies have proposed fine-tuning or training-free refinement methods for accurate text rendering. However, the critical…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Kanghyun Baek , Sangyub Lee , Jin Young Choi , Jaewoo Song , Daemin Park , Jooyoung Choi , Chaehun Shin , Bohyung Han , Sungroh Yoon

3D Gaussian Splatting based 3D editing has demonstrated impressive performance in recent years. However, the multi-view editing often exhibits significant local inconsistency, especially in areas of non-rigid deformation, which lead to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Minghao Wen , Shengjie Wu , Kangkan Wang , Dong Liang

Radiance Fields (RFs) have emerged as a crucial technology for 3D scene representation, enabling the synthesis of novel views with remarkable realism. However, as RFs become more widely used, the need for effective editing techniques that…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Yiren Lu , Jing Ma , Yu Yin

While image diffusion models have made significant progress in text-driven 3D content creation, they often fail to accurately capture the intended meaning of text prompts, especially for view information. This limitation leads to the Janus…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Zhipeng Hu , Minda Zhao , Chaoyi Zhao , Xinyue Liang , Lincheng Li , Zeng Zhao , Changjie Fan , Xiaowei Zhou , Xin Yu

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

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering high-quality, spatially consistent new views. While recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Jeong-gi Kwak , Erqun Dong , Yuhe Jin , Hanseok Ko , Shweta Mahajan , Kwang Moo Yi

Scene extrapolation -- the idea of generating novel views by flying into a given image -- is a promising, yet challenging task. For each predicted frame, a joint inpainting and 3D refinement problem has to be solved, which is ill posed and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Shengqu Cai , Eric Ryan Chan , Songyou Peng , Mohamad Shahbazi , Anton Obukhov , Luc Van Gool , Gordon Wetzstein

Despite recent progress in 3D-LLMs, they remain limited in accurately grounding language to visual and spatial elements in 3D environments. This limitation stems in part from training data that focuses on language reasoning rather than…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yue Zhang , Zun Wang , Han Lin , Jialu Li , Jianing Yang , Yonatan Bitton , Idan Szpektor , Mohit Bansal

We introduce MD-ProjTex, a method for fast and consistent text-guided texture generation for 3D shapes using pretrained text-to-image diffusion models. At the core of our approach is a multi-view consistency mechanism in UV space, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Ahmet Burak Yildirim , Mustafa Utku Aydogdu , Duygu Ceylan , Aysegul Dundar

Recent advancements in text-to-3D generation have significantly contributed to the automation and democratization of 3D content creation. Building upon these developments, we aim to address the limitations of current methods in blending…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Yeongtak Oh , Jooyoung Choi , Yongsung Kim , Minjun Park , Chaehun Shin , Sungroh Yoon

Temporal consistency is essential for video editing applications. Existing work on layered representation of videos allows propagating edits consistently to each frame. These methods, however, can only edit object appearance rather than…

Computer Vision and Pattern Recognition · Computer Science 2023-01-31 Yao-Chih Lee , Ji-Ze Genevieve Jang , Yi-Ting Chen , Elizabeth Qiu , Jia-Bin Huang

3D editing plays a crucial role in editing and reusing existing 3D assets, thereby enhancing productivity. Recently, 3DGS-based methods have gained increasing attention due to their efficient rendering and flexibility. However, achieving…

Graphics · Computer Science 2024-12-12 Yian Zhao , Wanshi Xu , Yang Wu , Weiheng Huang , Zhongqian Sun , Wei Yang

In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiaolong Li , Jiawei Mo , Ying Wang , Chethan Parameshwara , Xiaohan Fei , Ashwin Swaminathan , CJ Taylor , Zhuowen Tu , Paolo Favaro , Stefano Soatto

Diffusion-based Image Editing has achieved significant success in recent years. However, it remains challenging to achieve high-quality image editing while maintaining the background similarity without sacrificing speed or memory…

Graphics · Computer Science 2025-09-03 Siyi Liu , Weiming Chen , Yushun Tang , Zhihai He

This paper presents GaussEdit, a framework for adaptive 3D scene editing guided by text and image prompts. GaussEdit leverages 3D Gaussian Splatting as its backbone for scene representation, enabling convenient Region of Interest selection…

Graphics · Computer Science 2025-10-01 Zhenyu Shu , Junlong Yu , Kai Chao , Shiqing Xin , Ligang Liu

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 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