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Related papers: Improving Virtual Try-On with Garment-focused Diff…

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Diffusion models have become a new generative paradigm for text generation. Considering the discrete categorical nature of text, in this paper, we propose GlyphDiffusion, a novel diffusion approach for text generation via text-guided image…

Computation and Language · Computer Science 2023-05-09 Junyi Li , Wayne Xin Zhao , Jian-Yun Nie , Ji-Rong Wen

Studies of virtual try-on (VITON) have been shown their effectiveness in utilizing the generative neural network for virtually exploring fashion products, and some of recent researches of VITON attempted to synthesize human image wearing…

Computer Vision and Pattern Recognition · Computer Science 2022-05-11 Soonchan Park , Jinah Park

The remarkable progress in 3D face reconstruction has resulted in high-detail and photorealistic facial representations. Recently, Diffusion Models have revolutionized the capabilities of generative methods by surpassing the performance of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Stathis Galanakis , Alexandros Lattas , Stylianos Moschoglou , Stefanos Zafeiriou

Virtual try-on systems have significant potential in e-commerce, allowing customers to visualize garments on themselves. Existing image-based methods fall into two categories: those that directly warp garment-images onto person-images…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Kosuke Takemoto , Takafumi Koshinaka

The burgeoning field of camouflaged object detection (COD) seeks to identify objects that blend into their surroundings. Despite the impressive performance of recent models, we have identified a limitation in their robustness, where…

Computer Vision and Pattern Recognition · Computer Science 2023-04-13 Xue-Jing Luo , Shuo Wang , Zongwei Wu , Christos Sakaridis , Yun Cheng , Deng-Ping Fan , Luc Van Gool

Diffusion models have fundamentally transformed the field of generative models, making the assessment of similarity between customized model outputs and reference inputs critically important. However, traditional perceptual similarity…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Yiren Song , Xiaokang Liu , Mike Zheng Shou

Image retouching aims to enhance the visual quality of photos. Considering the different aesthetic preferences of users, the target of retouching is subjective. However, current retouching methods mostly adopt deterministic models, which…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Zheng-Peng Duan , Jiawei zhang , Zheng Lin , Xin Jin , Dongqing Zou , Chunle Guo , Chongyi Li

We present a data-driven method for learning to generate animations of 3D garments using a 2D image diffusion model. In contrast to existing methods, typically based on fully connected networks, graph neural networks, or generative…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Raquel Vidaurre , Elena Garces , Dan Casas

Recently, large-scale diffusion models, e.g., Stable diffusion and DallE2, have shown remarkable results on image synthesis. On the other hand, large-scale cross-modal pre-trained models (e.g., CLIP, ALIGN, and FILIP) are competent for…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Runhui Huang , Jianhua Han , Guansong Lu , Xiaodan Liang , Yihan Zeng , Wei Zhang , Hang Xu

Recent advancements in text-to-image diffusion models have significantly transformed visual content generation, yet their application in specialized fields such as interior design remains underexplored. In this paper, we present…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Zhaowei Wang , Ying Hao , Hao Wei , Qing Xiao , Lulu Chen , Yulong Li , Yue Yang , Tianyi Li

Diffusion models have achieved significant success in image and video generation. This motivates a growing interest in video editing tasks, where videos are edited according to provided text descriptions. However, most existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Zhen Xing , Qi Dai , Zihao Zhang , Hui Zhang , Han Hu , Zuxuan Wu , Yu-Gang Jiang

Existing image-based virtual try-on (VTON) methods primarily focus on single-layer or multi-garment VTON, neglecting multi-layer VTON (ML-VTON), which involves dressing multiple layers of garments onto the human body with realistic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Yang Yu , Yunze Deng , Yige Zhang , Yanjie Xiao , Youkun Ou , Wenhao Hu , Mingchao Li , Bin Feng , Wenyu Liu , Dandan Zheng , Jingdong Chen

Accurate and controllable image editing is a challenging task that has attracted significant attention recently. Notably, DragGAN is an interactive point-based image editing framework that achieves impressive editing results with…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Yujun Shi , Chuhui Xue , Jun Hao Liew , Jiachun Pan , Hanshu Yan , Wenqing Zhang , Vincent Y. F. Tan , Song Bai

Generating a virtual try-on image from in-shop clothing images and a model person's snapshot is a challenging task because the human body and clothes have high flexibility in their shapes. In this paper, we develop a Virtual Try-on…

Computer Vision and Pattern Recognition · Computer Science 2019-11-20 Shion Honda

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

Generative Adversarial Networks (GANs) dominate the research field in image-based virtual try-on, but have not resolved problems such as unnatural deformation of garments and the blurry generation quality. While the generative quality of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Jianhao Zeng , Dan Song , Weizhi Nie , Hongshuo Tian , Tongtong Wang , Anan Liu

The development of online economics arouses the demand of generating images of models on product clothes, to display new clothes and promote sales. However, the expensive proprietary model images challenge the existing image virtual try-on…

Computer Vision and Pattern Recognition · Computer Science 2021-12-15 Ruili Feng , Cheng Ma , Chengji Shen , Xin Gao , Zhenjiang Liu , Xiaobo Li , Kairi Ou , Zhengjun Zha

Denosing diffusion model, as a generative model, has received a lot of attention in the field of image generation recently, thanks to its powerful generation capability. However, diffusion models have not yet received sufficient research in…

Computer Vision and Pattern Recognition · Computer Science 2023-04-12 ZiHan Cao , ShiQi Cao , Xiao Wu , JunMing Hou , Ran Ran , Liang-Jian Deng

Diffusion models (DMs) have become the new trend of generative models and have demonstrated a powerful ability of conditional synthesis. Among those, text-to-image diffusion models pre-trained on large-scale image-text pairs are highly…

Computer Vision and Pattern Recognition · Computer Science 2023-03-06 Wenliang Zhao , Yongming Rao , Zuyan Liu , Benlin Liu , Jie Zhou , Jiwen Lu

Virtual try-on systems have long been hindered by heavy reliance on human body masks, limited fine-grained control over garment attributes, and poor generalization to real-world, in-the-wild scenarios. In this paper, we propose JCo-MVTON…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Aowen Wang , Wei Li , Hao Luo , Mengxing Ao , Chenyu Zhu , Xinyang Li , Fan Wang