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The fashion e-commerce industry has witnessed significant growth in recent years, prompting exploring image-based virtual try-on techniques to incorporate Augmented Reality (AR) experiences into online shopping platforms. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Khoi-Nguyen Nguyen-Ngoc , Thanh-Tung Phan-Nguyen , Khanh-Duy Le , Tam V. Nguyen , Minh-Triet Tran , Trung-Nghia Le

Recent advancements in text-guided diffusion models have unlocked powerful image manipulation capabilities, yet balancing reconstruction fidelity and editability for real images remains a significant challenge. In this work, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Yangyang Xu , Wenqi Shao , Yong Du , Haiming Zhu , Yang Zhou , Ping Luo , Shengfeng He

Recent text-to-image (T2I) models have benefited from large-scale and high-quality data, demonstrating impressive performance. However, these T2I models still struggle to produce images that are aesthetically pleasing, geometrically…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Jianshu Guo , Wenhao Chai , Jie Deng , Hsiang-Wei Huang , Tian Ye , Yichen Xu , Jiawei Zhang , Jenq-Neng Hwang , Gaoang Wang

Recently, large-scale text-to-image (T2I) diffusion models have emerged as a powerful tool for image-to-image translation (I2I), allowing open-domain image translation via user-provided text prompts. This paper proposes frequency-controlled…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Xiang Gao , Zhengbo Xu , Junhan Zhao , Jiaying Liu

Applying diffusion models to image-to-image translation (I2I) has recently received increasing attention due to its practical applications. Previous attempts inject information from the source image into each denoising step for an iterative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Mengfei Xia , Yu Zhou , Ran Yi , Yong-Jin Liu , Wenping Wang

In this study, we explore Transformer-based diffusion models for image and video generation. Despite the dominance of Transformer architectures in various fields due to their flexibility and scalability, the visual generative domain…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Shoufa Chen , Mengmeng Xu , Jiawei Ren , Yuren Cong , Sen He , Yanping Xie , Animesh Sinha , Ping Luo , Tao Xiang , Juan-Manuel Perez-Rua

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

The issue of generative pretraining for vision models has persisted as a long-standing conundrum. At present, the text-to-image (T2I) diffusion model demonstrates remarkable proficiency in generating high-definition images matching textual…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Qiang Wan , Zilong Huang , Bingyi Kang , Jiashi Feng , Li Zhang

Scalable Vector Graphics (SVGs) are highly favored by designers due to their resolution independence and well-organized layer structure. Although existing text-to-vector (T2V) generation methods can create SVGs from text prompts, they often…

Graphics · Computer Science 2025-05-16 Peiying Zhang , Nanxuan Zhao , Jing Liao

Diffusion Transformer (DiT), a promising diffusion model for visual generation, demonstrates impressive performance but incurs significant computational overhead. Intriguingly, analysis of pre-trained DiT models reveals that global…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Yuang Ai , Qihang Fan , Xuefeng Hu , Zhenheng Yang , Ran He , Huaibo Huang

Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolution (SR). However, most existing T2I diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Brian B. Moser , Stanislav Frolov , Tobias C. Nauen , Federico Raue , Andreas Dengel

We present a method to create diffusion-based video models from pretrained Text-to-Image (T2I) models. Recently, AnimateDiff proposed freezing the T2I model while only training temporal layers. We advance this method by proposing a unique…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Mingi Kwon , Seoung Wug Oh , Yang Zhou , Difan Liu , Joon-Young Lee , Haoran Cai , Baqiao Liu , Feng Liu , Youngjung Uh

Video try-on replaces clothing in videos with target garments. Existing methods struggle to generate high-quality and temporally consistent results when handling complex clothing patterns and diverse body poses. We present 3DV-TON, a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Min Wei , Chaohui Yu , Jingkai Zhou , Fan Wang

We present Fashion-VDM, a video diffusion model (VDM) for generating virtual try-on videos. Given an input garment image and person video, our method aims to generate a high-quality try-on video of the person wearing the given garment,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Johanna Karras , Yingwei Li , Nan Liu , Luyang Zhu , Innfarn Yoo , Andreas Lugmayr , Chris Lee , Ira Kemelmacher-Shlizerman

The most advanced text-to-image (T2I) models require significant training costs (e.g., millions of GPU hours), seriously hindering the fundamental innovation for the AIGC community while increasing CO2 emissions. This paper introduces…

Computer Vision and Pattern Recognition · Computer Science 2024-01-01 Junsong Chen , Jincheng Yu , Chongjian Ge , Lewei Yao , Enze Xie , Yue Wu , Zhongdao Wang , James Kwok , Ping Luo , Huchuan Lu , Zhenguo Li

Video virtual try-on aims to replace the clothing of a person in a video with a target garment. Current dual-branch architectures have achieved significant success in diffusion models based on the U-Net; however, adapting them to diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Yanjie Pan , Qingdong He , Lidong Wang , Bo Peng , Mingmin Chi

This paper does not describe a new method; instead, it provides a thorough exploration of an important yet understudied design space related to recent advances in text-to-image synthesis -- specifically, the deep fusion of large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Bingda Tang , Boyang Zheng , Xichen Pan , Sayak Paul , Saining Xie

While recent advances in virtual try-on (VTON) have achieved realistic garment transfer to human subjects, its inverse task, virtual try-off (VTOFF), which aims to reconstruct canonical garment templates from dressed humans, remains…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Angang Zhang , Fang Deng , Hao Chen , Zhongjian Chen , Junyan Li

Diffusion models have gained tremendous success in text-to-image generation, yet still lag behind with visual understanding tasks, an area dominated by autoregressive vision-language models. We propose a large-scale and fully end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Zijie Li , Henry Li , Yichun Shi , Amir Barati Farimani , Yuval Kluger , Linjie Yang , Peng Wang

Recent large-scale vision-language models (VLMs) have shown remarkable text-to-image generation capabilities, yet their visual fidelity remains constrained by the discrete image tokenization, which poses a major challenge. Although several…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Ji Woo Hong , Hee Suk Yoon , Gwanhyeong Koo , Eunseop Yoon , SooHwan Eom , Qi Dai , Chong Luo , Chang D. Yoo
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