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In this paper, we propose LSRNA, a novel framework for higher-resolution (exceeding 1K) image generation using diffusion models by leveraging super-resolution directly in the latent space. Existing diffusion models struggle with scaling…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Jinho Jeong , Sangmin Han , Jinwoo Kim , Seon Joo Kim

Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. However, restricted control flexibility and limited prompt…

Graphics · Computer Science 2025-06-04 Dongyu Yan , Leyi Wu , Jiantao Lin , Luozhou Wang , Tianshuo Xu , Zhifei Chen , Zhen Yang , Lie Xu , Shunsi Zhang , Yingcong Chen

This paper introduces innovative solutions to enhance spatial controllability in diffusion models reliant on text queries. We first introduce vision guidance as a foundational spatial cue within the perturbed distribution. This…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zipeng Qi , Guoxi Huang , Chenyang Liu , Fei Ye

Diffusion generative models have recently greatly improved the power of text-conditioned image generation. Existing image generation models mainly include text conditional diffusion model and cross-modal guided diffusion model, which are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Wei Li , Xue Xu , Xinyan Xiao , Jiachen Liu , Hu Yang , Guohao Li , Zhanpeng Wang , Zhifan Feng , Qiaoqiao She , Yajuan Lyu , Hua Wu

The field of advanced text-to-image generation is witnessing the emergence of unified frameworks that integrate powerful text encoders, such as CLIP and T5, with Diffusion Transformer backbones. Although there have been efforts to control…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Liang Chen , Shuai Bai , Wenhao Chai , Weichu Xie , Haozhe Zhao , Leon Vinci , Junyang Lin , Baobao Chang

Recent diffusion-based generative models show promise in their ability to generate text images, but limitations in specifying the styles of the generated texts render them insufficient in the realm of typographic design. This paper proposes…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 KhayTze Peong , Seiichi Uchida , Daichi Haraguchi

High-resolution image generation with Generative Artificial Intelligence (GenAI) has immense potential but, due to the enormous capital investment required for training, it is increasingly centralised to a few large corporations, and hidden…

Computer Vision and Pattern Recognition · Computer Science 2023-12-18 Ruoyi Du , Dongliang Chang , Timothy Hospedales , Yi-Zhe Song , Zhanyu Ma

In this age of information, images are a critical medium for storing and transmitting information. With the rapid growth of image data amount, visual compression and visual data perception are two important research topics attracting a lot…

Image and Video Processing · Electrical Eng. & Systems 2024-07-02 Yuefeng Zhang , Chuanmin Jia , Jiannhui Chang , Siwei Ma

The three areas of realistic forward rendering, per-pixel inverse rendering, and generative image synthesis may seem like separate and unrelated sub-fields of graphics and vision. However, recent work has demonstrated improved estimation of…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Zheng Zeng , Valentin Deschaintre , Iliyan Georgiev , Yannick Hold-Geoffroy , Yiwei Hu , Fujun Luan , Ling-Qi Yan , Miloš Hašan

The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Yichen Sun , Zhixuan Chu , Zhan Qin , Kui Ren

As latent diffusion models (LDMs) democratize image generation capabilities, there is a growing need to detect fake images. A good detector should focus on the generative models fingerprints while ignoring image properties such as semantic…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Anirudh Sundara Rajan , Utkarsh Ojha , Jedidiah Schloesser , Yong Jae Lee

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion model. Learning a video diffusion model in the latent space…

Computer Vision and Pattern Recognition · Computer Science 2023-04-19 Jie An , Songyang Zhang , Harry Yang , Sonal Gupta , Jia-Bin Huang , Jiebo Luo , Xi Yin

The stochastic formation of defects during Laser Powder Bed Fusion (L-PBF) negatively impacts its adoption for high-precision use cases. Optical monitoring techniques can be used to identify defects based on layer-wise imaging, but these…

Image and Video Processing · Electrical Eng. & Systems 2024-09-23 Francis Ogoke , Sumesh Kalambettu Suresh , Jesse Adamczyk , Dan Bolintineanu , Anthony Garland , Michael Heiden , Amir Barati Farimani

Generating complete 360-degree panoramas from narrow field of view images is ongoing research as omnidirectional RGB data is not readily available. Existing GAN-based approaches face some barriers to achieving higher quality output, and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Tianhao Wu , Chuanxia Zheng , Tat-Jen Cham

The increasing demand for 3D assets across various industries necessitates efficient and automated methods for 3D content creation. Leveraging 3D Gaussian Splatting, recent large reconstruction models (LRMs) have demonstrated the ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Jingrui Ye , Lingting Zhu , Runze Zhang , Zeyu Hu , Yingda Yin , Lanjiong Li , Lequan Yu , Qingmin Liao

Driven by the scalable diffusion models trained on large-scale datasets, text-to-image synthesis methods have shown compelling results. However, these models still fail to precisely follow the text prompt involving multiple objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Quynh Phung , Songwei Ge , Jia-Bin Huang

Scene graphs offer a structured, hierarchical representation of images, with nodes and edges symbolizing objects and the relationships among them. It can serve as a natural interface for image editing, dramatically improving precision and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Zhiyuan Zhang , DongDong Chen , Jing Liao

The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users. The intended generation can be expressed in natural language, with the model producing faithful…

Recent unified image generation models have achieved remarkable success by employing MLLMs for semantic understanding and diffusion backbones for image generation. However, these models remain fundamentally limited in spatially-aware tasks…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Haiyi Qiu , Kaihang Pan , Jiacheng Li , Juncheng Li , Siliang Tang , Yueting Zhuang