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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

Controllable video generation has attracted significant attention, largely due to advances in video diffusion models. In domains such as autonomous driving, it is essential to develop highly accurate predictions for object motions. This…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ge Ya Luo , Zhi Hao Luo , Anthony Gosselin , Alexia Jolicoeur-Martineau , Christopher Pal

The field of generative models has recently witnessed significant progress, with diffusion models showing remarkable performance in image generation. In light of this success, there is a growing interest in exploring the application of…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ariel Lapid , Idan Achituve , Lior Bracha , Ethan Fetaya

Despite the remarkable process of talking-head-based avatar-creating solutions, directly generating anchor-style videos with full-body motions remains challenging. In this study, we propose Make-Your-Anchor, a novel system necessitating…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Ziyao Huang , Fan Tang , Yong Zhang , Xiaodong Cun , Juan Cao , Jintao Li , Tong-Yee Lee

Virtual try-on (VTON) has recently achieved impressive visual fidelity, but most existing systems require uploading personal photos to cloud-based GPUs, raising privacy concerns and limiting on-device deployment. To address this, we present…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Zhenchen Wan , Ce Chen , Runqi Lin , Jiaxin Huang , Tianxi Chen , Yanwu Xu , Tongliang Liu , Mingming Gong

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem

Compared to images, videos better reflect real-world acquisition and possess valuable temporal cues. However, existing multi-sensor fusion research predominantly integrates complementary context from multiple images rather than videos due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Linfeng Tang , Yeda Wang , Meiqi Gong , Zizhuo Li , Yuxin Deng , Xunpeng Yi , Chunyu Li , Han Xu , Hao Zhang , Jiayi Ma

The availability of large-scale multimodal datasets and advancements in diffusion models have significantly accelerated progress in 4D content generation. Most prior approaches rely on multiple image or video diffusion models, utilizing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Hanwen Liang , Yuyang Yin , Dejia Xu , Hanxue Liang , Zhangyang Wang , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

Motivated by discrete diffusion's success in language-vision modeling, we explore its potential for multi-view generation, a task dominated by continuous approaches. We introduce ViewMask-1-to-3, formulating multi-view synthesis as a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Ruishu Zhu , Zhihao Huang , Jiacheng Sun , Ping Luo , Hongyuan Zhang , Xuelong Li

Virtual clothes try-on has emerged as a vital feature in online shopping, offering consumers a critical tool to visualize how clothing fits. In our research, we introduce an innovative approach for virtual clothes try-on, utilizing a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Lingxiao Lu , Shengyi Wu , Haoxuan Sun , Junhong Gou , Jianlou Si , Chen Qian , Jianfu Zhang , Liqing Zhang

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

3D content creation via text-driven stylization has played a fundamental challenge to multimedia and graphics community. Recent advances of cross-modal foundation models (e.g., CLIP) have made this problem feasible. Those approaches…

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

Virtual try-on (VTON) transfers a target clothing image to a reference person, where clothing fidelity is a key requirement for downstream e-commerce applications. However, existing VTON methods still fall short in high-fidelity try-on due…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Han Yang , Yanlong Zang , Ziwei Liu

Virtual Try-On (VTON) technology allows users to visualize how clothes would look on them without physically trying them on, gaining traction with the rise of digitalization and online shopping. Traditional VTON methods, often using…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Seohyun Lee , Jintae Park , Sanghyeok Park

Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we use for training and how to ensure multi-view consistency.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Qi Zuo , Xiaodong Gu , Lingteng Qiu , Yuan Dong , Zhengyi Zhao , Weihao Yuan , Rui Peng , Siyu Zhu , Zilong Dong , Liefeng Bo , Qixing Huang

The recent availability and adaptability of text-to-image models has sparked a new era in many related domains that benefit from the learned text priors as well as high-quality and fast generation capabilities, one of which is texture…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Raphael Bensadoun , Yanir Kleiman , Idan Azuri , Omri Harosh , Andrea Vedaldi , Natalia Neverova , Oran Gafni

In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Mengyang Feng , Jinlin Liu , Kai Yu , Yuan Yao , Zheng Hui , Xiefan Guo , Xianhui Lin , Haolan Xue , Chen Shi , Xiaowen Li , Aojie Li , Xiaoyang Kang , Biwen Lei , Miaomiao Cui , Peiran Ren , Xuansong Xie

Robotic manipulation requires understanding both the 3D spatial structure of the environment and its temporal evolution, yet most existing policies overlook one or both. They typically rely on 2D visual observations and backbones pretrained…

In this paper, we tackle a new task of 3D object synthesis, where a 3D model is composited with another object category to create a novel 3D model. However, most existing text/image/3D-to-3D methods struggle to effectively integrate…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zeren Xiong , Zikun Chen , Zedong Zhang , Xiang Li , Ying Tai , Jian Yang , Jun Li

Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, we aim to enhance the quality and functionality of these…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xiyi Chen , Marko Mihajlovic , Shaofei Wang , Sergey Prokudin , Siyu Tang