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With advances in the quality of text-to-image (T2I) models has come interest in benchmarking their prompt faithfulness -- the semantic coherence of generated images to the prompts they were conditioned on. A variety of T2I faithfulness…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Michael Saxon , Fatima Jahara , Mahsa Khoshnoodi , Yujie Lu , Aditya Sharma , William Yang Wang

Recently text-to-image models have gained widespread attention in the community due to their controllable and high-quality generation ability. However, the robustness of such models and their potential ethical issues have not been fully…

Cryptography and Security · Computer Science 2024-02-14 Shengfang Zhai , Weilong Wang , Jiajun Li , Yinpeng Dong , Hang Su , Qingni Shen

There has been a drastic growth of research in Generative Adversarial Nets (GANs) in the past few years. Proposed in 2014, GAN has been applied to various applications such as computer vision and natural language processing, and achieves…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 He Huang , Philip S. Yu , Changhu Wang

Despite extensive recent advances in summary generation models, evaluation of auto-generated summaries still widely relies on single-score systems insufficient for transparent assessment and in-depth qualitative analysis. Towards bridging…

Computation and Language · Computer Science 2022-10-26 Ben Schaper , Christopher Lohse , Marcell Streile , Andrea Giovannini , Richard Osuala

Content creation, central to applications such as virtual reality, can be a tedious and time-consuming. Recent image synthesis methods simplify this task by offering tools to generate new views from as little as a single input image, or by…

Computer Vision and Pattern Recognition · Computer Science 2020-10-05 Tewodros Habtegebrial , Varun Jampani , Orazio Gallo , Didier Stricker

Text-to-image (TTI) diffusion models have demonstrated impressive results in generating high-resolution images of complex and imaginative scenes. Recent approaches have further extended these methods with personalization techniques that…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Tanzila Rahman , Shweta Mahajan , Hsin-Ying Lee , Jian Ren , Sergey Tulyakov , Leonid Sigal

Research in Image Generation has recently made significant progress, particularly boosted by the introduction of Vision-Language models which are able to produce high-quality visual content based on textual inputs. Despite ongoing…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Federico Betti , Jacopo Staiano , Lorenzo Baraldi , Lorenzo Baraldi , Rita Cucchiara , Nicu Sebe

Despite their wide-spread success, Text-to-Image models (T2I) still struggle to produce images that are both aesthetically pleasing and faithful to the user's input text. We introduce DreamSync, a model-agnostic training algorithm by design…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Jiao Sun , Deqing Fu , Yushi Hu , Su Wang , Royi Rassin , Da-Cheng Juan , Dana Alon , Charles Herrmann , Sjoerd van Steenkiste , Ranjay Krishna , Cyrus Rashtchian

Modern text-to-image synthesis models have achieved an exceptional level of photorealism, generating high-quality images from arbitrary text descriptions. In light of the impressive synthesis ability, several studies have exhibited…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Joonghyuk Shin , Minguk Kang , Jaesik Park

This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Chenshuang Zhang , Chaoning Zhang , Mengchun Zhang , In So Kweon , Junmo Kim

We propose a method for scene-level sketch-to-photo synthesis with text guidance. Although object-level sketch-to-photo synthesis has been widely studied, whole-scene synthesis is still challenging without reference photos that adequately…

Computer Vision and Pattern Recognition · Computer Science 2023-02-15 AprilPyone MaungMaung , Makoto Shing , Kentaro Mitsui , Kei Sawada , Fumio Okura

Recent progress in text-to-image (T2I) models enables high-quality image generation with flexible textual control. To utilize the abundant visual priors in the off-the-shelf T2I models, a series of methods try to invert an image to proper…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Zijie Wu , Chaohui Yu , Zhen Zhu , Fan Wang , Xiang Bai

Interleaved text-and-image generation has been an intriguing research direction, where the models are required to generate both images and text pieces in an arbitrary order. Despite the emerging advancements in interleaved generation, the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Minqian Liu , Zhiyang Xu , Zihao Lin , Trevor Ashby , Joy Rimchala , Jiaxin Zhang , Lifu Huang

Subject-driven text-to-image diffusion models empower users to tailor the model to new concepts absent in the pre-training dataset using a few sample images. However, prevalent subject-driven models primarily rely on single-concept input…

Computer Vision and Pattern Recognition · Computer Science 2024-02-16 Junjie Shentu , Matthew Watson , Noura Al Moubayed

Semantic communication, as a revolutionary communication architecture, is considered a promising novel communication paradigm. Unlike traditional symbol-based error-free communication systems, semantic-based visual communication systems…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Senran Fan , Zhicheng Bao , Chen Dong , Haotai Liang , Xiaodong Xu , Ping Zhang

Text-to-image generation intends to automatically produce a photo-realistic image, conditioned on a textual description. It can be potentially employed in the field of art creation, data augmentation, photo-editing, etc. Although many…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Zhenxing Zhang , Lambert Schomaker

In this paper, we focus on generating realistic images from text descriptions. Current methods first generate an initial image with rough shape and color, and then refine the initial image to a high-resolution one. Most existing…

Computer Vision and Pattern Recognition · Computer Science 2019-04-03 Minfeng Zhu , Pingbo Pan , Wei Chen , Yi Yang

Currently, high-fidelity text-to-image models are developed in an accelerating pace. Among them, Diffusion Models have led to a remarkable improvement in the quality of image generation, making it vary challenging to distinguish between…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Ziyue Zeng , Haoyuan Liu , Dingjie Peng , Luoxu Jing , Hiroshi Watanabe

This paper addresses the performance bottlenecks of existing text-driven image generation methods in terms of semantic alignment accuracy and structural consistency. A high-fidelity image generation method is proposed by integrating…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Danyi Gao

Text-to-image models take a sentence (i.e., prompt) and generate images associated with this input prompt. These models have created award wining-art, videos, and even synthetic datasets. However, text-to-image (T2I) models can generate…

Computation and Language · Computer Science 2023-06-12 Alexander Lin , Lucas Monteiro Paes , Sree Harsha Tanneru , Suraj Srinivas , Himabindu Lakkaraju