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Image generation has recently seen tremendous advances, with diffusion models allowing to synthesize convincing images for a large variety of text prompts. In this article, we propose DiffEdit, a method to take advantage of text-conditioned…

Computer Vision and Pattern Recognition · Computer Science 2022-10-21 Guillaume Couairon , Jakob Verbeek , Holger Schwenk , Matthieu Cord

The exponential progress in generative AI poses serious implications for the credibility of all real images and videos. There will exist a point in the future where 1) digital content produced by generative AI will be indistinguishable from…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Alexander Vilesov , Yuan Tian , Nader Sehatbakhsh , Achuta Kadambi

Recent advancements in machine learning, particularly in deep learning and object detection, have significantly improved performance in various tasks, including image classification and synthesis. However, challenges persist, particularly…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Jan Lippemeier , Stefanie Hittmeyer , Oliver Niehörster , Markus Lange-Hegermann

Scene text erasing seeks to erase text contents from scene images and current state-of-the-art text erasing models are trained on large-scale synthetic data. Although data synthetic engines can provide vast amounts of annotated training…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Xiangcheng Du , Zhao Zhou , Yingbin Zheng , Xingjiao Wu , Tianlong Ma , Cheng Jin

Synthetic images generated from deep generative models have the potential to address data scarcity and data privacy issues. The selection of synthesis models is mostly based on image quality measurements, and most researchers favor…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Xiaodan Xing , Federico Felder , Yang Nan , Giorgos Papanastasiou , Walsh Simon , Guang Yang

In the current era, image manipulation is becoming increasingly easier, yielding more natural looking images, owing to the modern tools in image processing and computer vision techniques. The task of the segregation of forged images has…

Computer Vision and Pattern Recognition · Computer Science 2019-11-20 Akash Kumar , Arnav Bhavsar

With recent text-to-image models, anyone can generate deceptively realistic images with arbitrary contents, fueling the growing threat of visual disinformation. A key enabler for generating high-resolution images with low computational cost…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Jonas Ricker , Denis Lukovnikov , Asja Fischer

Prior art has shown it is possible to estimate, through image processing and computer vision techniques, the types and parameters of transformations that have been applied to the content of individual images to obtain new images. Given a…

Computer Vision and Pattern Recognition · Computer Science 2018-01-24 Daniel Moreira , Aparna Bharati , Joel Brogan , Allan Pinto , Michael Parowski , Kevin W. Bowyer , Patrick J. Flynn , Anderson Rocha , Walter J. Scheirer

Detecting manipulated images has become a significant emerging challenge. The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being…

Computer Vision and Pattern Recognition · Computer Science 2019-11-26 Peng Zhou , Bor-Chun Chen , Xintong Han , Mahyar Najibi , Abhinav Shrivastava , Ser Nam Lim , Larry S. Davis

Diffusion-based image compression has demonstrated impressive perceptual performance. However, it suffers from two critical drawbacks: (1) excessive decoding latency due to multi-step sampling, and (2) poor fidelity resulting from…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Zheng Chen , Mingde Zhou , Jinpei Guo , Jiale Yuan , Yifei Ji , Yulun Zhang

Text-to-image diffusion models have demonstrated remarkable effectiveness in rapid and high-fidelity personalization, even when provided with only a few user images. However, the effectiveness of personalization techniques has lead to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Naresh Kumar Devulapally , Shruti Agarwal , Tejas Gokhale , Vishnu Suresh Lokhande

Diffusion models generate images with an unprecedented level of quality, but how can we freely rearrange image layouts? Recent works generate controllable scenes via learning spatially disentangled latent codes, but these methods do not…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Jiawei Ren , Mengmeng Xu , Jui-Chieh Wu , Ziwei Liu , Tao Xiang , Antoine Toisoul

Image generation algorithms are increasingly integral to diverse aspects of human society, driven by their practical applications. However, insufficient oversight in artificial Intelligence generated content (AIGC) can facilitate the spread…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Wenhao Luo , Zhangyi Shen , Ye Yao , Feng Ding , Guopu Zhu , Weizhi Meng

Hard coatings play a critical role in industry, with ceramic materials offering outstanding hardness and thermal stability for applications that demand superior mechanical performance. However, deploying artificial intelligence (AI) for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Binwei Chen , Huachao Leng , Chi Yeung Mang , Tsz Wai Cheung , Yanhua Chen , Wai Keung Anthony Loh , Chi Ho Wong , Chak Yin Tang

Text-to-image generation models that generate images based on prompt descriptions have attracted an increasing amount of attention during the past few months. Despite their encouraging performance, these models raise concerns about the…

Cryptography and Security · Computer Science 2023-01-10 Zeyang Sha , Zheng Li , Ning Yu , Yang Zhang

Guided image synthesis enables everyday users to create and edit photo-realistic images with minimum effort. The key challenge is balancing faithfulness to the user input (e.g., hand-drawn colored strokes) and realism of the synthesized…

Computer Vision and Pattern Recognition · Computer Science 2022-01-06 Chenlin Meng , Yutong He , Yang Song , Jiaming Song , Jiajun Wu , Jun-Yan Zhu , Stefano Ermon

Recent advances in generative AI have led to the development of techniques to generate visually realistic synthetic video. While a number of techniques have been developed to detect AI-generated synthetic images, in this paper we show that…

Computer Vision and Pattern Recognition · Computer Science 2024-04-25 Danial Samadi Vahdati , Tai D. Nguyen , Aref Azizpour , Matthew C. Stamm

We present Stable Video Diffusion - a latent video diffusion model for high-resolution, state-of-the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained for 2D image synthesis have been turned into…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Andreas Blattmann , Tim Dockhorn , Sumith Kulal , Daniel Mendelevitch , Maciej Kilian , Dominik Lorenz , Yam Levi , Zion English , Vikram Voleti , Adam Letts , Varun Jampani , Robin Rombach

Text-to-image diffusion models have demonstrated a remarkable ability to generate photorealistic images from natural language prompts. These high-resolution, language-guided synthesized images are essential for the explainability of disease…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Zahra TehraniNasab , Amar Kumar , Tal Arbel

While image forensics is concerned with whether an image has been tampered with, image anti-forensics attempts to prevent image forensics methods from detecting tampered images. The competition between these two fields started long before…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Eren Tahir , Mert Bal
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