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Related papers: T2IW: Joint Text to Image & Watermark Generation

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Recent advances in large-scale text-to-image generation models have led to a surge in subject-driven text-to-image generation, which aims to produce customized images that align with textual descriptions while preserving the identity of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Kewen Chen , Xiaobin Hu , Wenqi Ren

With the continuous advancement of image generation technology, advanced models such as GPT-Image-1 and Qwen-Image have achieved remarkable text-to-image consistency and world knowledge However, these models still fall short in…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Junyan Ye , Leiqi Zhu , Yuncheng Guo , Dongzhi Jiang , Zilong Huang , Yifan Zhang , Zhiyuan Yan , Haohuan Fu , Conghui He , Weijia Li

The ethical need to protect AI-generated content has been a significant concern in recent years. While existing watermarking strategies have demonstrated success in detecting synthetic content (detection), there has been limited exploration…

Cryptography and Security · Computer Science 2024-07-17 Rui Min , Sen Li , Hongyang Chen , Minhao Cheng

Modern text-to-image (T2I) diffusion models can generate images with remarkable realism and creativity. These advancements have sparked research in fake image detection and attribution, yet prior studies have not fully explored the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Katherine Xu , Lingzhi Zhang , Jianbo Shi

Recent advances in text-to-image diffusion models have enabled the photorealistic generation of images from text prompts. Despite the great progress, existing models still struggle to generate compositional multi-concept images naturally,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Hazarapet Tunanyan , Dejia Xu , Shant Navasardyan , Zhangyang Wang , Humphrey Shi

Text-to-image models are known to struggle with generating images that perfectly align with textual prompts. Several previous studies have focused on evaluating image-text alignment in text-to-image generation. However, these evaluations…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Huixuan Zhang , Xiaojun Wan

A significant ``modality gap" exists between the abundance of text-only data and the increasing power of multimodal models. This work systematically investigates whether images generated on-the-fly by Text-to-Image (T2I) models can serve as…

Multimedia · Computer Science 2026-03-04 Yuesheng Huang , Peng Zhang , Xiaoxin Wu , Riliang Liu , Jiaqi Liang

Text-to-Image (T2I) diffusion models are widely recognized for their ability to generate high-quality and diverse images based on text prompts. However, despite recent advances, these models are still prone to generating unsafe images…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Jiangweizhi Peng , Zhiwei Tang , Gaowen Liu , Charles Fleming , Mingyi Hong

With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, the generated contents cannot be fully controlled. There is a potential risk that T2I model can generate unsafe images…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Dong Han , Salaheldin Mohamed , Yong Li

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

Uncertainty quantification in text-to-image (T2I) generative models is crucial for understanding model behavior and improving output reliability. In this paper, we are the first to quantify and evaluate the uncertainty of T2I models with…

Artificial Intelligence · Computer Science 2024-12-05 Gianni Franchi , Dat Nguyen Trong , Nacim Belkhir , Guoxuan Xia , Andrea Pilzer

Text-to-image diffusion models, such as Stable Diffusion, have shown exceptional potential in generating high-quality images. However, recent studies highlight concerns over the use of unauthorized data in training these models, which may…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Soumil Datta , Shih-Chieh Dai , Leo Yu , Guanhong Tao

Text-to-Image (T2I) generation is enabling new applications that support creators, designers, and general end users of productivity software by generating illustrative content with high photorealism starting from a given descriptive text as…

Computers and Society · Computer Science 2023-04-14 Ranjita Naik , Besmira Nushi

Unifying text-image contrastive learning and text-to-image (T2I) generation in a single end-to-end model is challenging because the two objectives demand opposing masking regimes: contrastive alignment needs near-complete visible tokens,…

The proliferation of AI-generated images has intensified the need for robust content authentication methods. We present InvisMark, a novel watermarking technique designed for high-resolution AI-generated images. Our approach leverages…

Cryptography and Security · Computer Science 2024-11-21 Rui Xu , Mengya Hu , Deren Lei , Yaxi Li , David Lowe , Alex Gorevski , Mingyu Wang , Emily Ching , Alex Deng

Recent progress in text-to-image (T2I) generation underscores the importance of reliable benchmarks in evaluating how accurately generated images reflect the semantics of their textual prompt. However, (1) existing benchmarks lack the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yibin Wang , Zhimin Li , Yuhang Zang , Jiazi Bu , Yujie Zhou , Yi Xin , Junjun He , Chunyu Wang , Qinglin Lu , Cheng Jin , Jiaqi Wang

While synthetic data has proven effective for improving scientific reasoning in the text domain, multimodal reasoning remains constrained by the difficulty of synthesizing scientifically rigorous images. Existing Text-to-Image (T2I) models…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Honglin Lin , Chonghan Qin , Zheng Liu , Qizhi Pei , Yu Li , Zhanping Zhong , Xin Gao , Yanfeng Wang , Conghui He , Lijun Wu

In this paper, we present an end-to-end approach to generate high-resolution person images conditioned on texts only. State-of-the-art text-to-image generation models are mainly designed for center-object generation, e.g., flowers and…

Computer Vision and Pattern Recognition · Computer Science 2023-07-04 Deyin Liu , Lin Yuanbo Wu , Bo Li , Zongyuan Ge

The transformative potential of text-to-image (T2I) models hinges on their ability to synthesize culturally diverse, photorealistic images from textual prompts. However, these models often perpetuate cultural biases embedded within their…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Muna Numan Said , Aarib Zaidi , Rabia Usman , Sonia Okon , Praneeth Medepalli , Kevin Zhu , Vasu Sharma , Sean O'Brien

Text-to-image (T2I) models have achieved remarkable progress, yet they continue to struggle with complex prompts that require simultaneously handling multiple objects, relations, and attributes. Existing inference-time strategies, such as…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Shantanu Jaiswal , Mihir Prabhudesai , Nikash Bhardwaj , Zheyang Qin , Amir Zadeh , Chuan Li , Katerina Fragkiadaki , Deepak Pathak
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