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Existing 3D editing methods rely on computationally intensive scene-by-scene iterative optimization and suffer from multi-view inconsistency. We propose an effective and feed-forward 3D editing framework based on the TRELLIS generative…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Shimin Hu , Yuanyi Wei , Fei Zha , Yudong Guo , Juyong Zhang

3D texture swapping allows for the customization of 3D object textures, enabling efficient and versatile visual transformations in 3D editing. While no dedicated method exists, adapted 2D editing and text-driven 3D editing approaches can…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Xiao Cao , Beibei Lin , Bo Wang , Zhiyong Huang , Robby T. Tan

Generating realistic 3D scenes is an area of growing interest in computer vision and robotics. However, creating high-quality, diverse synthetic 3D content often requires expert intervention, making it costly and complex. Recently, efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Siyi Hu , Diego Martin Arroyo , Stephanie Debats , Fabian Manhardt , Luca Carlone , Federico Tombari

3D vector graphics play a crucial role in various applications including 3D shape retrieval, conceptual design, and virtual reality interactions due to their ability to capture essential structural information with minimal representation.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Chuang Wang , Haitao Zhou , Ling Luo , Qian Yu

Generative models for 3D object synthesis have seen significant advancements with the incorporation of prior knowledge distilled from 2D diffusion models. Nevertheless, challenges persist in the form of multi-view geometric inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Lincong Feng , Muyu Wang , Maoyu Wang , Kuo Xu , Xiaoli Liu

Discrete diffusion models have recently shown great promise for modeling complex discrete data, with masked diffusion models (MDMs) offering a compelling trade-off between quality and generation speed. MDMs denoise by progressively…

Machine Learning · Computer Science 2026-04-15 Tianyu Xie , Shuchen Xue , Zijin Feng , Tianyang Hu , Jiacheng Sun , Zhenguo Li , Cheng Zhang

Novel-view synthesis through diffusion models has demonstrated remarkable potential for generating diverse and high-quality images. Yet, the independent process of image generation in these prevailing methods leads to challenges in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-01 Xianghui Yang , Yan Zuo , Sameera Ramasinghe , Loris Bazzani , Gil Avraham , Anton van den Hengel

Direct mesh editing and deformation are key components in the geometric modeling and animation pipeline. Mesh editing methods are typically framed as optimization problems combining user-specified vertex constraints with a regularizer that…

Graphics · Computer Science 2024-08-05 Tianhao Xie , Eugene Belilovsky , Sudhir Mudur , Tiberiu Popa

This paper proposes Instruct 4D-to-4D that achieves 4D awareness and spatial-temporal consistency for 2D diffusion models to generate high-quality instruction-guided dynamic scene editing results. Traditional applications of 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Linzhan Mou , Jun-Kun Chen , Yu-Xiong Wang

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

With the help of Score Distillation Sampling (SDS) and the rapid development of neural 3D representations, some methods have been proposed to perform 3D editing such as adding additional geometries, or overwriting textures. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Yige Chen , Teng Hu , Yizhe Tang , Siyuan Chen , Ang Chen , Ran Yi

View transformation robustness (VTR) is critical for deep-learning-based multi-view 3D object reconstruction models, which indicates the methods' stability under inputs with various view transformations. However, existing research seldom…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Qi Zhang , Zhouhang Luo , Tao Yu , Hui Huang

With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye

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

The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Hongkun Zhang , Zherong Pan , Congyi Zhang , Lifeng Zhu , Xifeng Gao

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

3D-aware image synthesis aims to generate images of objects from multiple views by learning a 3D representation. However, one key challenge remains: existing approaches lack geometry constraints, hence usually fail to generate multi-view…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Xuanmeng Zhang , Zhedong Zheng , Daiheng Gao , Bang Zhang , Pan Pan , Yi Yang

Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand in stark contrast to the compact, structured, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuan Li , Cheng Lin , Yuan Liu , Xiaoxiao Long , Chenxu Zhang , Ningna Wang , Xin Li , Wenping Wang , Xiaohu Guo

3D editing - the task of locally modifying the geometry or appearance of a 3D asset - has wide applications in immersive content creation, digital entertainment, and AR/VR. However, unlike 2D editing, it remains challenging due to the need…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Ruihao Xia , Yang Tang , Pan Zhou

Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, especially in the paradigm of 2D diffusion that lacks 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Chong-Wah Ngo , Tao Mei