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Related papers: ShapeFusion: A 3D diffusion model for localized sh…

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Diffusion models have emerged as a popular method for 3D generation. However, it is still challenging for diffusion models to efficiently generate diverse and high-quality 3D shapes. In this paper, we introduce OctFusion, which can generate…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Bojun Xiong , Si-Tong Wei , Xin-Yang Zheng , Yan-Pei Cao , Zhouhui Lian , Peng-Shuai Wang

3D human pose estimation from 2D images is a challenging problem due to depth ambiguity and occlusion. Because of these challenges the task is underdetermined, where there exists multiple -- possibly infinite -- poses that are plausible…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Francis Snelgar , Ming Xu , Stephen Gould , Liang Zheng , Akshay Asthana

In this paper, we propose a novel diffusion-based multi-condition controllable framework for video head swapping, which seamlessly transplant a human head from a static image into a dynamic video, while preserving the original body and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Chaonan Ji , Jinwei Qi , Peng Zhang , Bang Zhang , Liefeng Bo

Face editing modifies the appearance of face, which plays a key role in customization and enhancement of personal images. Although much work have achieved remarkable success in text-driven face editing, they still face significant…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Xin Zhang , Siting Huang , Xiangyang Luo , Yifan Xie , Weijiang Yu , Heng Chang , Fei Ma , Fei Yu

We introduce PolyDiff, the first diffusion-based approach capable of directly generating realistic and diverse 3D polygonal meshes. In contrast to methods that use alternate 3D shape representations (e.g. implicit representations), our…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Antonio Alliegro , Yawar Siddiqui , Tatiana Tommasi , Matthias Nießner

Diffusion models arise as a powerful generative tool recently. Despite the great progress, existing diffusion models mainly focus on uni-modal control, i.e., the diffusion process is driven by only one modality of condition. To further…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Ziqi Huang , Kelvin C. K. Chan , Yuming Jiang , Ziwei Liu

Diffusion models emerged as a leading approach in text-to-image generation, producing high-quality images from textual descriptions. However, attempting to achieve detailed control to get a desired image solely through text remains a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-12 Pablo Domingo-Gregorio , Javier Ruiz-Hidalgo

Physically-based simulation is a powerful approach for 3D facial animation as the resulting deformations are governed by physical constraints, allowing to easily resolve self-collisions, respond to external forces and perform realistic…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Lingchen Yang , Gaspard Zoss , Prashanth Chandran , Markus Gross , Barbara Solenthaler , Eftychios Sifakis , Derek Bradley

Text driven diffusion models have shown remarkable capabilities in editing images. However, when editing 3D scenes, existing works mostly rely on training a NeRF for 3D editing. Recent NeRF editing methods leverages edit operations by…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Vivek Madhavaram , Shivangana Rawat , Chaitanya Devaguptapu , Charu Sharma , Manohar Kaul

Image diffusion models, trained on massive image collections, have emerged as the most versatile image generator model in terms of quality and diversity. They support inverting real images and conditional (e.g., text) generation, making…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Duygu Ceylan , Chun-Hao Paul Huang , Niloy J. Mitra

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

The rapid advancement of pretrained text-driven diffusion models has significantly enriched applications in image generation and editing. However, as the demand for personalized content editing increases, new challenges emerge especially…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Rui Jiang , Xinghe Fu , Guangcong Zheng , Teng Li , Taiping Yao , Xi Li

Hairstyle transfer is a challenging task in the image editing field that modifies the hairstyle of a given face image while preserving its other appearance and background features. The existing hairstyle transfer approaches heavily rely on…

Computer Vision and Pattern Recognition · Computer Science 2024-12-23 Chaeyeon Chung , Sunghyun Park , Jeongho Kim , Jaegul Choo

We propose a novel approach for probabilistic generative modeling of 3D shapes. Unlike most existing models that learn to deterministically translate a latent vector to a shape, our model, Point-Voxel Diffusion (PVD), is a unified,…

Computer Vision and Pattern Recognition · Computer Science 2021-08-31 Linqi Zhou , Yilun Du , Jiajun Wu

Recent advances in deep generative modeling have unlocked unprecedented opportunities for video synthesis. In real-world applications, however, users often seek tools to faithfully realize their creative editing intentions with precise and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yuhao Liu , Tengfei Wang , Fang Liu , Zhenwei Wang , Rynson W. H. Lau

Recent advances in diffusion models have significantly improved image editing. However, challenges persist in handling geometric transformations, such as translation, rotation, and scaling, particularly in complex scenes. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Shuo Zhang , Wenzhuo Wu , Huayu Zhang , Jiarong Cheng , Xianghao Zang , Chao Ban , Hao Sun , Zhongjiang He , Tianwei Cao , Kongming Liang , Zhanyu Ma

Recent generative models can create visually plausible 3D representations of objects. However, the generation process often allows for implicit control signals, such as contextual descriptions, and rarely supports bold geometric distortions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Changwoon Choi , Hyunsoo Lee , Clément Jambon , Yael Vinker , Young Min Kim

As 3D generation techniques continue to flourish, the demand for generating personalized content is rapidly rising. Users increasingly seek to apply various editing methods to polish generated 3D content, aiming to enhance its color, style,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Weitao Wang , Haoran Xu , Jun Meng , Haoqian Wang

Parametric Computer-Aided Design (CAD) is fundamental to modern 3D modeling, yet existing methods struggle to generate long command sequences, especially under complex geometric and topological dependencies. Transformer-based architectures…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Xiaolei Zhou , Chuangjie Fang , Jie Wu , Jingyi Yang , Boyi Lin , Jianwei Zheng

There is a growing demand for the accessible creation of high-quality 3D avatars that are animatable and customizable. Although 3D morphable models provide intuitive control for editing and animation, and robustness for single-view face…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Connor Z. Lin , Koki Nagano , Jan Kautz , Eric R. Chan , Umar Iqbal , Leonidas Guibas , Gordon Wetzstein , Sameh Khamis