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We present a novel image editing scenario termed Text-grounded Object Generation (TOG), defined as generating a new object in the real image spatially conditioned by textual descriptions. Existing diffusion models exhibit limitations of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Xiangtian Xue , Jiasong Wu , Youyong Kong , Lotfi Senhadji , Huazhong Shu

Visual generation grounded in Visual Foundation Model (VFM) representations offers a highly promising unified pathway for integrating visual understanding, perception, and generation. Despite this potential, training large-scale…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Minglei Shi , Haolin Wang , Borui Zhang , Wenzhao Zheng , Bohan Zeng , Ziyang Yuan , Xiaoshi Wu , Yuanxing Zhang , Huan Yang , Xintao Wang , Pengfei Wan , Kun Gai , Jie Zhou , Jiwen Lu

Diffusion models have made tremendous progress in text-driven image and video generation. Now text-to-image foundation models are widely applied to various downstream image synthesis tasks, such as controllable image generation and image…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Fengyuan Shi , Jiaxi Gu , Hang Xu , Songcen Xu , Wei Zhang , Limin Wang

A plethora of text-guided image editing methods has recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models especially Stable Diffusion. Despite the success of diffusion models in…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Qihe Pan , Zhen Zhao , Zicheng Wang , Sifan Long , Yiming Wu , Wei Ji , Haoran Liang , Ronghua Liang

Diffusion models are generative models with impressive text-to-image synthesis capabilities and have spurred a new wave of creative methods for classical machine learning tasks. However, the best way to harness the perceptual knowledge of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Neehar Kondapaneni , Markus Marks , Manuel Knott , Rogerio Guimaraes , Pietro Perona

Text-to-video (T2V) generation has recently garnered significant attention thanks to the large multi-modality model Sora. However, T2V generation still faces two important challenges: 1) Lacking a precise open sourced high-quality dataset.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Kepan Nan , Rui Xie , Penghao Zhou , Tiehan Fan , Zhenheng Yang , Zhijie Chen , Xiang Li , Jian Yang , Ying Tai

Subject-driven text-to-image (T2I) generation aims to produce images that align with a given textual description, while preserving the visual identity from a referenced subject image. Despite its broad downstream applicability - ranging…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Aviv Slobodkin , Hagai Taitelbaum , Yonatan Bitton , Brian Gordon , Michal Sokolik , Nitzan Bitton Guetta , Almog Gueta , Royi Rassin , Dani Lischinski , Idan Szpektor

Text-to-image diffusion models have shown impressive capabilities in generating realistic visuals from natural-language prompts, yet they often struggle with accurately binding attributes to corresponding objects, especially in prompts…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Do Huu Dat , Nam Hyeonu , Po-Yuan Mao , Tae-Hyun Oh

Large-scale text-guided image diffusion models have shown astonishing results in text-to-image (T2I) generation. However, applying these models to synthesize textures for 3D geometries remains challenging due to the domain gap between 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Jiawei Lu , Yingpeng Zhang , Zengjun Zhao , He Wang , Kun Zhou , Tianjia Shao

Over the past few years, Text-to-Image (T2I) generation approaches based on diffusion models have gained significant attention. However, vanilla diffusion models often suffer from spelling inaccuracies in the text displayed within the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Sanyam Lakhanpal , Shivang Chopra , Vinija Jain , Aman Chadha , Man Luo

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

Video generation models are revolutionizing content creation, with image-to-video models drawing increasing attention due to their enhanced controllability, visual consistency, and practical applications. However, despite their popularity,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Wenhao Wang , Yi Yang

Video composition is the core task of video editing. Although image composition based on diffusion models has been highly successful, it is not straightforward to extend the achievement to video object composition tasks, which not only…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Wei Wang , Yaosen Chen , Yuegen Liu , Qi Yuan , Shubin Yang , Yanru Zhang

Text-guided diffusion models such as DALLE-2, Imagen, eDiff-I, and Stable Diffusion are able to generate an effectively endless variety of images given only a short text prompt describing the desired image content. In many cases the images…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Wan-Duo Kurt Ma , J. P. Lewis , Avisek Lahiri , Thomas Leung , W. Bastiaan Kleijn

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Image-to-video (I2V) generation tasks always suffer from keeping high fidelity in the open domains. Traditional image animation techniques primarily focus on specific domains such as faces or human poses, making them difficult to generalize…

Computer Vision and Pattern Recognition · Computer Science 2024-03-06 Weijie Li , Litong Gong , Yiran Zhu , Fanda Fan , Biao Wang , Tiezheng Ge , Bo Zheng

Subject-driven image generation (SDIG) aims to manipulate specific subjects within images while adhering to textual instructions, a task crucial for advancing text-to-image diffusion models. SDIG requires reconciling the tension between…

Computer Vision and Pattern Recognition · Computer Science 2025-09-19 Jibai Lin , Bo Ma , Yating Yang , Xi Zhou , Rong Ma , Turghun Osman , Ahtamjan Ahmat , Rui Dong , Lei Wang

Large-scale text-to-image (T2I) diffusion models have been extended for text-guided video editing, yielding impressive zero-shot video editing performance. Nonetheless, the generated videos usually show spatial irregularities and temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Yuanzhi Wang , Yong Li , Xiaoya Zhang , Xin Liu , Anbo Dai , Antoni B. Chan , Zhen Cui

Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

The rapid progress of image-guided video generation (I2V) has raised concerns about its potential misuse in misinformation and fraud, underscoring the urgent need for effective digital watermarking. While existing watermarking methods…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Guanjie Wang , Zehua Ma , Han Fang , Weiming Zhang