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Existing diffusion-based methods have achieved impressive results in human motion editing. However, these methods often exhibit significant ghosting and body distortion in unseen in-the-wild cases. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Yi Zuo , Lingling Li , Licheng Jiao , Fang Liu , Xu Liu , Wenping Ma , Shuyuan Yang , Yuwei Guo

Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. However, these interfaces lack precise control, and the associated methods typically specialize…

We propose a novel diffusion-based framework for reconstructing 3D geometry of hand-held objects from monocular RGB images by leveraging hand-object interaction as geometric guidance. Our method conditions a latent diffusion model on an…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Ayce Idil Aytekin , Helge Rhodin , Rishabh Dabral , Christian Theobalt

In the realm of 3D computer vision, parametric models have emerged as a ground-breaking methodology for the creation of realistic and expressive 3D avatars. Traditionally, they rely on Principal Component Analysis (PCA), given its ability…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Rolandos Alexandros Potamias , Michail Tarasiou , Stylianos Ploumpis , Stefanos Zafeiriou

Image completion techniques have made significant progress in filling missing regions (i.e., holes) in images. However, large-hole completion remains challenging due to limited structural information. In this paper, we address this problem…

Computer Vision and Pattern Recognition · Computer Science 2023-09-07 Daichi Horita , Jiaolong Yang , Dong Chen , Yuki Koyama , Kiyoharu Aizawa , Nicu Sebe

Vision-centric autonomous driving systems require diverse data for robust training and evaluation, which can be augmented by manipulating object positions and appearances within existing scene captures. While recent advancements in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Yiyuan Liang , Zhiying Yan , Liqun Chen , Jiahuan Zhou , Luxin Yan , Sheng Zhong , Xu Zou

We present a novel framework for generating photorealistic 3D human head and subsequently manipulating and reposing them with remarkable flexibility. The proposed approach leverages an implicit function representation of 3D human heads,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Yushi Lan , Feitong Tan , Di Qiu , Qiangeng Xu , Kyle Genova , Zeng Huang , Sean Fanello , Rohit Pandey , Thomas Funkhouser , Chen Change Loy , Yinda Zhang

Diffusion models have attained remarkable success in the domains of image generation and editing. It is widely recognized that employing larger inversion and denoising steps in diffusion model leads to improved image reconstruction quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Chen Hou , Guoqiang Wei , Zhibo Chen

Recently, several point-based image editing methods (e.g., DragDiffusion, FreeDrag, DragNoise) have emerged, yielding precise and high-quality results based on user instructions. However, these methods often make insufficient use of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 DuoSheng Chen , Binghui Chen , Yifeng Geng , Liefeng Bo

Recently, text-to-image (T2I) editing has been greatly pushed forward by applying diffusion models. Despite the visual promise of the generated images, inconsistencies with the expected textual prompt remain prevalent. This paper aims to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Aoxue Li , Mingyang Yi , Zhenguo Li

Fashion image editing is a crucial tool for designers to convey their creative ideas by visualizing design concepts interactively. Current fashion image editing techniques, though advanced with multimodal prompts and powerful diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Xiaolong Wang , Zhi-Qi Cheng , Jue Wang , Xiaojiang Peng

Distilling 3D representations from pretrained 2D diffusion models is essential for 3D creative applications across gaming, film, and interior design. Current SDS-based methods are hindered by inefficient information distillation from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Haoran Li , Yuli Tian , Yonghui Wang , Yong Liao , Lin Wang , Yuyang Wang , Peng Yuan Zhou

Recent research explores the potential of Diffusion Models (DMs) for consistent object editing, which aims to modify object position, size, and composition, etc., while preserving the consistency of objects and background without changing…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Liyao Jiang , Negar Hassanpour , Mohammad Salameh , Mohammadreza Samadi , Jiao He , Fengyu Sun , Di Niu

Relighting a person from a single photo is an attractive but ill-posed task, as a 2D image ambiguously entangles 3D geometry, intrinsic appearance, and illumination. Current methods either use sequential pipelines that suffer from error…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Yuxuan Xue , Ruofan Liang , Egor Zakharov , Timur Bagautdinov , Chen Cao , Giljoo Nam , Shunsuke Saito , Gerard Pons-Moll , Javier Romero

Diffusion models have emerged as powerful tools for a wide range of vision tasks, including text-guided image generation and editing. In this work, we explore their potential for object grounding in remote sensing imagery. We propose a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Geet Sethi , Panav Shah , Ashutosh Gandhe , Soumitra Darshan Nayak

Text-to-image generative models have made remarkable advancements in generating high-quality images. However, generated images often contain undesirable artifacts or other errors due to model limitations. Existing techniques to fine-tune…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Peyman Gholami , Robert Xiao

We present a diffusion-based video editing framework, namely DiffusionAtlas, which can achieve both frame consistency and high fidelity in editing video object appearance. Despite the success in image editing, diffusion models still…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Shao-Yu Chang , Hwann-Tzong Chen , Tyng-Luh Liu

This paper explores image editing under the joint control of text and drag interactions. While recent advances in text-driven and drag-driven editing have achieved remarkable progress, they suffer from complementary limitations: text-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Qihang Wang , Yaxiong Wang , Lechao Cheng , Zhun Zhong

In the realm of image generation, the quest for realism and customization has never been more pressing. While existing methods like concept sliders have made strides, they often falter when it comes to no-AIGC images, particularly images…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Yufei Tang , Daiheng Gao , Pingyu Wu , Wenbo Zhou , Bang Zhang , Weiming Zhang

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang
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