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The creation of high-quality 3D assets is paramount for applications in digital heritage preservation, entertainment, and robotics. Traditionally, this process necessitates skilled professionals and specialized software for the modeling,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Shen Chen , Jiale Zhou , Zhongyu Jiang , Tianfang Zhang , Zongkai Wu , Jenq-Neng Hwang , Lei Li

The controllability of 3D object generation methods is achieved through input text. Existing text-to-3D object generation methods primarily focus on generating a single object based on a single object description. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Shaorong Sun , Shuchao Pang , Yazhou Yao , Xiaoshui Huang

Although the recent rapid evolution of 3D generative neural networks greatly improves 3D shape generation, it is still not convenient for ordinary users to create 3D shapes and control the local geometry of generated shapes. To address…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Xin-Yang Zheng , Hao Pan , Peng-Shuai Wang , Xin Tong , Yang Liu , Heung-Yeung Shum

Precise geometric control in image generation is essential for engineering \& product design and creative industries to control 3D object features accurately in image space. Traditional 3D editing approaches are time-consuming and demand…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Phillip Mueller , Talip Uenlue , Sebastian Schmidt , Marcel Kollovieh , Jiajie Fan , Stephan Guennemann , Lars Mikelsons

Recent years have witnessed the strong power of 3D generation models, which offer a new level of creative flexibility by allowing users to guide the 3D content generation process through a single image or natural language. However, it…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Fangfu Liu , Hanyang Wang , Weiliang Chen , Haowen Sun , Yueqi Duan

Creating and editing the shape and color of 3D objects require tremendous human effort and expertise. Compared to direct manipulation in 3D interfaces, 2D interactions such as sketches and scribbles are usually much more natural and…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Zezhou Cheng , Menglei Chai , Jian Ren , Hsin-Ying Lee , Kyle Olszewski , Zeng Huang , Subhransu Maji , Sergey Tulyakov

We present 3DiFACE, a novel method for personalized speech-driven 3D facial animation and editing. While existing methods deterministically predict facial animations from speech, they overlook the inherent one-to-many relationship between…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Balamurugan Thambiraja , Sadegh Aliakbarian , Darren Cosker , Justus Thies

Recent 3D generative models can synthesize high-quality assets, but their outputs are typically static: they lack the skeletal rigs, joint hierarchies, and skinning weights required for animation. This limits their use in games, film,…

Graphics · Computer Science 2026-05-14 Nikitas Chatzis , Marios Loizou , Evangelos Kalogerakis

Articulated 3D objects are central to many applications in robotics, AR/VR, and animation. Recent approaches to modeling such objects either rely on optimization-based reconstruction pipelines that require dense-view supervision or on…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Chuhao Chen , Isabella Liu , Xinyue Wei , Hao Su , Minghua Liu

Creating personalized 3D animations with precise control and realistic head motions remains challenging for current speech-driven 3D facial animation methods. Editing these animations is especially complex and time consuming, requires…

Graphics · Computer Science 2025-10-01 Balamurugan Thambiraja , Malte Prinzler , Sadegh Aliakbarian , Darren Cosker , Justus Thies

While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployability as afterthoughts. We present AssetGen, a 3D generator that focuses instead on these two…

Diffusion Handles is a novel approach to enabling 3D object edits on diffusion images. We accomplish these edits using existing pre-trained diffusion models, and 2D image depth estimation, without any fine-tuning or 3D object retrieval. The…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Karran Pandey , Paul Guerrero , Matheus Gadelha , Yannick Hold-Geoffroy , Karan Singh , Niloy Mitra

This paper proposes ProEdit - a simple yet effective framework for high-quality 3D scene editing guided by diffusion distillation in a novel progressive manner. Inspired by the crucial observation that multi-view inconsistency in scene…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Jun-Kun Chen , Yu-Xiong Wang

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

Despite the latest remarkable advances in generative modeling, efficient generation of high-quality 3D assets from textual prompts remains a difficult task. A key challenge lies in data scarcity: the most extensive 3D datasets encompass…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Antoine Mercier , Ramin Nakhli , Mahesh Reddy , Rajeev Yasarla , Hong Cai , Fatih Porikli , Guillaume Berger

Recent advancements in 3D generation are predominantly propelled by improvements in 3D-aware image diffusion models. These models are pretrained on Internet-scale image data and fine-tuned on massive 3D data, offering the capability of…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Zeyu Yang , Zijie Pan , Chun Gu , Li Zhang

Generating high-quality 3D assets from a given image is highly desirable in various applications such as AR/VR. Recent advances in single-image 3D generation explore feed-forward models that learn to infer the 3D model of an object without…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Yongwei Chen , Tengfei Wang , Tong Wu , Xingang Pan , Kui Jia , Ziwei Liu

The creation of manufacturable and editable 3D shapes through Computer-Aided Design (CAD) remains a highly manual and time-consuming task, hampered by the complex topology of boundary representations of 3D solids and unintuitive design…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Md Ferdous Alam , Faez Ahmed

Recent text-to-3D generation methods achieve impressive 3D content creation capacity thanks to the advances in image diffusion models and optimizing strategies. However, current methods struggle to generate correct 3D content for a complex…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Xinhua Cheng , Tianyu Yang , Jianan Wang , Yu Li , Lei Zhang , Jian Zhang , Li Yuan

Controllable generation is considered a potentially vital approach to address the challenge of annotating 3D data, and the precision of such controllable generation becomes particularly imperative in the context of data production for…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Jinhua Zhang , Hualian Sheng , Sijia Cai , Bing Deng , Qiao Liang , Wen Li , Ying Fu , Jieping Ye , Shuhang Gu