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Recent progress in image-to-3D has opened up immense possibilities for design, AR/VR, and robotics. However, to use AI-generated 3D assets in real applications, a critical requirement is the capability to edit them easily. We present a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ziqi Ma , Hongqiao Chen , Yisong Yue , Georgia Gkioxari

Based on recent advanced diffusion models, Text-to-image (T2I) generation models have demonstrated their capabilities to generate diverse and high-quality images. However, leveraging their potential for real-world content creation,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Sandra Zhang Ding , Jiafeng Mao , Kiyoharu Aizawa

3D scene generation conditioned on text prompts has significantly progressed due to the development of 2D diffusion generation models. However, the textual description of 3D scenes is inherently inaccurate and lacks fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Minglin Chen , Longguang Wang , Sheng Ao , Ye Zhang , Kai Xu , Yulan Guo

Large-scale text-to-video diffusion models have demonstrated an exceptional ability to synthesize diverse videos. However, due to the lack of extensive text-to-video datasets and the necessary computational resources for training, directly…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Nisha Huang , Yuxin Zhang , Weiming Dong

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

In image editing, it is essential to incorporate a context image to convey the user's precise requirements, such as subject appearance or image style. Existing training-based visual context-aware editing methods incur data collection effort…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Rui Song , Guo-Hua Wang , Qing-Guo Chen , Weihua Luo , Tongda Xu , Zhening Liu , Yan Wang , Zehong Lin , Jun Zhang

Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Shuai Yang , Yifan Zhou , Ziwei Liu , Chen Change Loy

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

One image to editable dynamic 3D model and video generation is novel direction and change in the research area of single image to 3D representation or 3D reconstruction of image. Gaussian Splatting has demonstrated its advantages in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinwei Lin

In autonomous driving, vision-centric 3D detection aims to identify 3D objects from images. However, high data collection costs and diverse real-world scenarios limit the scale of training data. Once distribution shifts occur between…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Hongbin Lin , Zilu Guo , Yifan Zhang , Shuaicheng Niu , Yafeng Li , Ruimao Zhang , Shuguang Cui , Zhen Li

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

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

Large scale text-guided diffusion models have garnered significant attention due to their ability to synthesize diverse images that convey complex visual concepts. This generative power has more recently been leveraged to perform text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-09-20 Etai Sella , Gal Fiebelman , Peter Hedman , Hadar Averbuch-Elor

Text-to-image (T2I) customization aims to create images that embody specific visual concepts delineated in textual descriptions. However, existing works still face a main challenge, concept overfitting. To tackle this challenge, we first…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Weili Zeng , Yichao Yan , Qi Zhu , Zhuo Chen , Pengzhi Chu , Weiming Zhao , Xiaokang Yang

Recently, impressive results have been achieved in 3D scene editing with text instructions based on a 2D diffusion model. However, current diffusion models primarily generate images by predicting noise in the latent space, and the editing…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Junjie Wang , Jiemin Fang , Xiaopeng Zhang , Lingxi Xie , Qi Tian

We propose a method for editing NeRF scenes with text-instructions. Given a NeRF of a scene and the collection of images used to reconstruct it, our method uses an image-conditioned diffusion model (InstructPix2Pix) to iteratively edit the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Ayaan Haque , Matthew Tancik , Alexei A. Efros , Aleksander Holynski , Angjoo Kanazawa

Open-domain 3D object synthesis has been lagging behind image synthesis due to limited data and higher computational complexity. To bridge this gap, recent works have investigated multi-view diffusion but often fall short in either 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Hansheng Chen , Ruoxi Shi , Yulin Liu , Bokui Shen , Jiayuan Gu , Gordon Wetzstein , Hao Su , Leonidas Guibas

Text-to-image (T2I) models have recently gained widespread adoption. This has spurred concerns about safeguarding intellectual property rights and an increasing demand for mechanisms that prevent the generation of specific artistic styles.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anand Kumar , Jiteng Mu , Nuno Vasconcelos

Text-conditioned image-to-video generation (TI2V) aims to synthesize a realistic video starting from a given image (e.g., a woman's photo) and a text description (e.g., "a woman is drinking water."). Existing TI2V frameworks often require…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Haomiao Ni , Bernhard Egger , Suhas Lohit , Anoop Cherian , Ye Wang , Toshiaki Koike-Akino , Sharon X. Huang , Tim K. Marks

Recent advancements in text-guided diffusion models have shown promise for general image editing via inversion techniques, but often struggle to maintain ID and structural consistency in real face editing tasks. To address this limitation,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yang Hou , Minggu Wang , Jianjun Zhao