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Current vision-language models (VLMs) are well-adapted for general visual understanding tasks. However, they perform inadequately when handling complex visual tasks related to human poses and actions due to the lack of specialized…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Dewen Zhang , Tahir Hussain , Wangpeng An , Hayaru Shouno

Large vision-language model (LVLM) based text-to-image (T2I) systems have become the dominant paradigm in image generation, yet whether they amplify social biases remains insufficiently understood. In this paper, we show that LVLM-based…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 NaHyeon Park , Namin An , Kunhee Kim , Soyeon Yoon , Jiahao Huo , Hyunjung Shim

When humans read a specific text, they often visualize the corresponding images, and we hope that computers can do the same. Text-to-image synthesis (T2I), which focuses on generating high-quality images from textual descriptions, has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Nonghai Zhang , Hao Tang

Current text-to-image (T2I) generation models struggle to align spatial composition with the input text, especially in complex scenes. Even layout-based approaches yield suboptimal spatial control, as their generation process is decoupled…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Zheyuan Liu , Munan Ning , Qihui Zhang , Shuo Yang , Zhongrui Wang , Yiwei Yang , Xianzhe Xu , Yibing Song , Weihua Chen , Fan Wang , Li Yuan

We introduce LLaVA-Reward, an efficient reward model designed to automatically evaluate text-to-image (T2I) generations across multiple perspectives, leveraging pretrained multimodal large language models (MLLMs). Existing MLLM-based…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Shijie Zhou , Ruiyi Zhang , Huaisheng Zhu , Branislav Kveton , Yufan Zhou , Jiuxiang Gu , Jian Chen , Changyou Chen

Current text-to-image generative models struggle to accurately represent object states (e.g., "a table without a bottle," "an empty tumbler"). In this work, we first design a fully-automatic pipeline to generate high-quality synthetic data…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Tianle Chen , Chaitanya Chakka , Deepti Ghadiyaram

Current image generation models produce visually compelling but scientifically implausible images, exposing a fundamental gap between visual fidelity and physical realism. In this work, we introduce ScienceT2I, an expert-annotated dataset…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Jialuo Li , Wenhao Chai , Xingyu Fu , Haiyang Xu , Saining Xie

Recently, Text-to-Image (T2I) generation models have achieved significant advancements. Correspondingly, many automated metrics have emerged to evaluate the image-text alignment capabilities of generative models. However, the performance…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Shuhao Han , Haotian Fan , Jiachen Fu , Liang Li , Tao Li , Junhui Cui , Yunqiu Wang , Yang Tai , Jingwei Sun , Chunle Guo , Chongyi Li

Text-to-image generation (T2I) refers to the text-guided generation of high-quality images. In the past few years, T2I has attracted widespread attention and numerous works have emerged. In this survey, we comprehensively review 141 works…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Pengfei Yang , Ngai-Man Cheung , Xinda Ma

Text-to-image (T2I) diffusion models have demonstrated impressive capabilities in generating high-quality images given a text prompt. However, ensuring the prompt-image alignment remains a considerable challenge, i.e., generating images…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Liyao Jiang , Negar Hassanpour , Mohammad Salameh , Mohan Sai Singamsetti , Fengyu Sun , Wei Lu , Di Niu

Inspired by the strong ties between vision and language, the two intimate human sensing and communication modalities, our paper aims to explore the generation of 3D human full-body motions from texts, as well as its reciprocal task,…

Computer Vision and Pattern Recognition · Computer Science 2022-08-08 Chuan Guo , Xinxin Zuo , Sen Wang , Li Cheng

Large language models (LLMs), such as GPT series and Llama series have demonstrated strong capabilities in natural language processing, contextual understanding, and text generation. In recent years, researchers are trying to enhance the…

Computation and Language · Computer Science 2024-10-08 Ziyang Chen , Stylios Moscholios

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

Text-to-image (T2I) generation has made remarkable progress, yet existing systems still lack intuitive control over spatial composition, object consistency, and multi-step editing. We present $\textbf{LayerCraft}$, a modular framework that…

Machine Learning · Computer Science 2025-10-20 Yuyao Zhang , Jinghao Li , Yu-Wing Tai

Text-to-motion (T2M) generation aims to control the behavior of a target character via textual descriptions. Leveraging text-motion paired datasets, existing T2M models have achieved impressive performance in generating high-quality motions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Jiakun Zheng , Ting Xiao , Shiqin Cao , Xinran Li , Zhe Wang , Chenjia Bai

Recent advancements in large language models have demonstrated how chain-of-thought (CoT) and reinforcement learning (RL) can improve performance. However, applying such reasoning strategies to the visual generation domain remains largely…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Dongzhi Jiang , Ziyu Guo , Renrui Zhang , Zhuofan Zong , Hao Li , Le Zhuo , Shilin Yan , Pheng-Ann Heng , Hongsheng Li

In the last two years, text-to-image diffusion models have become extremely popular. As their quality and usage increase, a major concern has been the need for better output control. In addition to prompt engineering, one effective method…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Clément Bonnet , Ariel N. Lee , Franck Wertel , Antoine Tamano , Tanguy Cizain , Pablo Ducru

Recent advancements in text-to-image models, particularly diffusion models, have shown significant promise. However, compositional text-to-image models frequently encounter difficulties in generating high-quality images that accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Song Wen , Guian Fang , Renrui Zhang , Peng Gao , Hao Dong , Dimitris Metaxas

Despite rapid advancements in the capabilities of generative models, pretrained text-to-image models still struggle in capturing the semantics conveyed by complex prompts that compound multiple objects and instance-level attributes.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Etai Sella , Yanir Kleiman , Hadar Averbuch-Elor

Recent spatial control methods for text-to-image (T2I) diffusion models have shown compelling results. However, these methods still fail to precisely follow the control conditions and generate the corresponding images, especially when…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Jiaze Wang , Rui Chen , Haowang Cui