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Related papers: CoProSketch: Controllable and Progressive Sketch G…

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Controllable image synthesis with user scribbles has gained huge public interest with the recent advent of text-conditioned latent diffusion models. The user scribbles control the color composition while the text prompt provides control…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Jaskirat Singh , Stephen Gould , Liang Zheng

EasyRead pictograms are simple, visually clear images that represent specific concepts and support comprehension for people with intellectual disabilities, low literacy, or language barriers. The large-scale production of EasyRead content…

Human-Computer Interaction · Computer Science 2026-03-17 Nicolas Dickenmann , Yanis Merzouki , Sonia Laguna , Thy Nowak-Tran , Emanuele Palumbo , Julia E. Vogt , Gerda Binder

Facial sketches are both a concise way of showing the identity of a person and a means to express artistic intention. While a few techniques have recently emerged that allow sketches to be extracted in different styles, they typically rely…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Kwan Yun , Kwanggyoon Seo , Chang Wook Seo , Soyeon Yoon , Seongcheol Kim , Soohyun Ji , Amirsaman Ashtari , Junyong Noh

Image composition targets at synthesizing a realistic composite image from a pair of foreground and background images. Recently, generative composition methods are built on large pretrained diffusion models to generate composite images,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Bo Zhang , Yuxuan Duan , Jun Lan , Yan Hong , Huijia Zhu , Weiqiang Wang , Li Niu

The requirement for 3D content is growing as AR/VR application emerges. At the same time, 3D modelling is only available for skillful experts, because traditional methods like Computer-Aided Design (CAD) are often too labor-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Ying Zang , Yidong Han , Chaotao Ding , Jianqi Zhang , Tianrun Chen

Recent advances in diffusion models have driven remarkable progress in image generation. However, the generation process remains computationally intensive, and users often need to iteratively refine prompts to achieve the desired results,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Yi Wei , Shunpu Tang , Liang Zhao , Qiangian Yang

Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditioning, however existing methods lack layout editing ability…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Alessandro Fontanella , Petru-Daniel Tudosiu , Yongxin Yang , Shifeng Zhang , Sarah Parisot

Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Lingjun Zhang , Xinyuan Chen , Yaohui Wang , Yue Lu , Yu Qiao

Text-to-image diffusion models are gradually introduced into computer graphics, recently enabling the development of Text-to-3D pipelines in an open domain. However, for interactive editing purposes, local manipulations of content through a…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Aryan Mikaeili , Or Perel , Mehdi Safaee , Daniel Cohen-Or , Ali Mahdavi-Amiri

Diffusion models have emerged as a powerful generative method, capable of producing stunning photo-realistic images from natural language descriptions. However, these models lack explicit control over the 3D structure in the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Wufei Ma , Qihao Liu , Jiahao Wang , Angtian Wang , Xiaoding Yuan , Yi Zhang , Zihao Xiao , Guofeng Zhang , Beijia Lu , Ruxiao Duan , Yongrui Qi , Adam Kortylewski , Yaoyao Liu , Alan Yuille

Personalizing generative models offers a way to guide image generation with user-provided references. Current personalization methods can invert an object or concept into the textual conditioning space and compose new natural sentences for…

Text-guided image editing has recently experienced rapid development. However, simultaneously performing multiple editing actions on a single image, such as background replacement and specific subject attribute changes, while maintaining…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Pengzhi Li , QInxuan Huang , Yikang Ding , Zhiheng Li

Controllable scene synthesis aims to create interactive environments for various industrial use cases. Scene graphs provide a highly suitable interface to facilitate these applications by abstracting the scene context in a compact manner.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Guangyao Zhai , Evin Pınar Örnek , Shun-Cheng Wu , Yan Di , Federico Tombari , Nassir Navab , Benjamin Busam

Diffusion models are a new class of generative models, and have dramatically promoted image generation with unprecedented quality and diversity. Existing diffusion models mainly try to reconstruct input image from a corrupted one with a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ling Yang , Jingwei Liu , Shenda Hong , Zhilong Zhang , Zhilin Huang , Zheming Cai , Wentao Zhang , Bin Cui

Large-scale generative models, such as text-to-image diffusion models, have garnered widespread attention across diverse domains due to their creative and high-fidelity image generation. Nonetheless, existing large-scale diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Younghyun Kim , Geunmin Hwang , Junyu Zhang , Eunbyung Park

ControlNet offers a powerful way to guide diffusion-based generative models, yet most implementations rely on ad-hoc heuristics to choose which network blocks to control-an approach that varies unpredictably with different tasks. To address…

Machine Learning · Computer Science 2025-02-21 Zheng Fang , Lichuan Xiang , Xu Cai , Kaicheng Zhou , Hongkai Wen

Text-to-image diffusion models can generate diverse content with flexible prompts, which makes them well-suited for customization through fine-tuning with a small amount of user-provided data. However, controllable fine-tuning that prevents…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Ziyao Zeng , Jingcheng Ni , Ruyi Liu , Alex Wong

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

The study of neural generative models of human sketches is a fascinating contemporary modeling problem due to the links between sketch image generation and the human drawing process. The landmark SketchRNN provided breakthrough by…

Computer Vision and Pattern Recognition · Computer Science 2020-07-15 Ayan Das , Yongxin Yang , Timothy Hospedales , Tao Xiang , Yi-Zhe Song

Leveraging the diffusion transformer (DiT) architecture, models like Sora, CogVideoX and Wan have achieved remarkable progress in text-to-video, image-to-video, and video editing tasks. Despite these advances, diffusion-based video…

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