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Recent advances in diffusion models have significantly improved audio-driven human video generation, surpassing traditional methods in both quality and controllability. However, existing approaches still face challenges in lip-sync…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Xingpei Ma , Shenneng Huang , Jiaran Cai , Yuansheng Guan , Shen Zheng , Hanfeng Zhao , Qiang Zhang , Shunsi Zhang

Recent works demonstrate a remarkable ability to customize text-to-image diffusion models while only providing a few example images. What happens if you try to customize such models using multiple, fine-grained concepts in a sequential…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 James Seale Smith , Yen-Chang Hsu , Lingyu Zhang , Ting Hua , Zsolt Kira , Yilin Shen , Hongxia Jin

Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Teng-Fang Hsiao , Bo-Kai Ruan , Yi-Lun Wu , Tzu-Ling Lin , Hong-Han Shuai

Optical illusion hidden picture is an interesting visual perceptual phenomenon where an image is cleverly integrated into another picture in a way that is not immediately obvious to the viewer. Established on the off-the-shelf text-to-image…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Xiang Gao , Shuai Yang , Jiaying Liu

Recent text-to-image personalization methods have shown great promise in teaching a diffusion model user-specified concepts given a few images for reusing the acquired concepts in a novel context. With massive efforts being dedicated to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Zhengyang Yu , Zhaoyuan Yang , Jing Zhang

Recent advancements in text-to-image (T2I) generative models have shown remarkable capabilities in producing diverse and imaginative visuals based on text prompts. Despite the advancement, these diffusion models sometimes struggle to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xiaohui Chen , Yongfei Liu , Yingxiang Yang , Jianbo Yuan , Quanzeng You , Li-Ping Liu , Hongxia Yang

Diffusion models have achieved impressive results in generative tasks for text-to-video (T2V) synthesis. However, achieving accurate text alignment in T2V generation remains challenging due to the complex temporal dependencies across…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Jaemin Kim , Bryan Sangwoo Kim , Jong Chul Ye

Recent advances in diffusion models have showcased promising results in the text-to-video (T2V) synthesis task. However, as these T2V models solely employ text as the guidance, they tend to struggle in modeling detailed temporal dynamics.…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Seungwoo Lee , Chaerin Kong , Donghyeon Jeon , Nojun Kwak

Text-to-Image (T2I) diffusion models have achieved remarkable success in image generation. Despite their progress, challenges remain in both prompt-following ability, image quality and lack of high-quality datasets, which are essential for…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Jingkun An , Yinghao Zhu , Zongjian Li , Enshen Zhou , Haoran Feng , Xijie Huang , Bohua Chen , Yemin Shi , Chengwei Pan

Text-to-image (T2I) diffusion models are popular for introducing image manipulation methods, such as editing, image fusion, inpainting, etc. At the same time, image-to-video (I2V) and text-to-video (T2V) models are also built on top of T2I…

With the impressive progress in diffusion-based text-to-image generation, extending such powerful generative ability to text-to-video raises enormous attention. Existing methods either require large-scale text-video pairs and a large number…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Ruiqi Wu , Liangyu Chen , Tong Yang , Chunle Guo , Chongyi Li , Xiangyu Zhang

Text-to-image (T2I) diffusion models have made significant strides in generating high-quality images. However, progressively manipulating certain attributes of generated images to meet the desired user expectations remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Weixin Ye , Hongguang Zhu , Wei Wang , Yahui Liu , Mengyu Wang , Xuecheng Nie

Creating editable videos that depict complex interactions between multiple objects in various artistic styles has long been a challenging task in filmmaking. Progress is often hampered by the scarcity of data sets that contain paired text…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Anisha Jain

Diffusion distillation has dramatically accelerated class-conditional image synthesis, but its applicability to open-ended text-to-image (T2I) generation is still unclear. We present the first systematic study that adapts and compares…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Yifan Pu , Yizeng Han , Zhiwei Tang , Jiasheng Tang , Fan Wang , Bohan Zhuang , Gao Huang

As scaling laws in generative AI push performance, they also simultaneously concentrate the development of these models among actors with large computational resources. With a focus on text-to-image (T2I) generative models, we aim to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Vikash Sehwag , Xianghao Kong , Jingtao Li , Michael Spranger , Lingjuan Lyu

Image animation has seen significant progress, driven by the powerful generative capabilities of diffusion models. However, maintaining appearance consistency with static input images and mitigating abrupt motion transitions in generated…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Xin Ma , Yaohui Wang , Genyun Jia , Xinyuan Chen , Tien-Tsin Wong , Cunjian Chen

Large text-to-image models achieved a remarkable leap in the evolution of AI, enabling high-quality and diverse synthesis of images from a given text prompt. However, these models lack the ability to mimic the appearance of subjects in a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Nataniel Ruiz , Yuanzhen Li , Varun Jampani , Yael Pritch , Michael Rubinstein , Kfir Aberman

Recently, the strong latent Diffusion Probabilistic Model (DPM) has been applied to high-quality Text-to-Image (T2I) generation (e.g., Stable Diffusion), by injecting the encoded target text prompt into the gradually denoised diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Mingyang Yi , Aoxue Li , Yi Xin , Zhenguo Li

Recent advances in diffusion-based text-to-video (T2V) models have demonstrated remarkable progress, but these models still face challenges in generating videos with multiple objects. Most models struggle with accurately capturing complex…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Aimon Rahman , Jiang Liu , Ze Wang , Ximeng Sun , Jialian Wu , Xiaodong Yu , Yusheng Su , Vishal M. Patel , Zicheng Liu , Emad Barsoum

Despite the rapid adoption of text-to-image (T2I) diffusion models, causal and representation-level analysis remains fragmented and largely limited to isolated probing techniques. To address this gap, we introduce DreamReader: a unified…

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