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Large scale text-guided diffusion models have garnered significant attention due to their ability to synthesize diverse images that convey complex visual concepts. This generative power has more recently been leveraged to perform text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-09-20 Etai Sella , Gal Fiebelman , Peter Hedman , Hadar Averbuch-Elor

We introduce MVGenMaster, a multi-view diffusion model enhanced with 3D priors to address versatile Novel View Synthesis (NVS) tasks. MVGenMaster leverages 3D priors that are warped using metric depth and camera poses, significantly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Chenjie Cao , Chaohui Yu , Shang Liu , Fan Wang , Xiangyang Xue , Yanwei Fu

Current image-to-3D approaches suffer from high computational costs and lack scalability for high-resolution outputs. In contrast, we introduce a novel framework to directly generate explicit surface geometry and texture using multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Haoyu Wu , Meher Gitika Karumuri , Chuhang Zou , Seungbae Bang , Yuelong Li , Dimitris Samaras , Sunil Hadap

We introduce Control4D, an innovative framework for editing dynamic 4D portraits using text instructions. Our method addresses the prevalent challenges in 4D editing, notably the inefficiencies of existing 4D representations and the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Ruizhi Shao , Jingxiang Sun , Cheng Peng , Zerong Zheng , Boyao Zhou , Hongwen Zhang , Yebin Liu

Recent months have witnessed rapid progress in 3D generation based on diffusion models. Most advances require fine-tuning existing 2D Stable Diffsuions into multi-view settings or tedious distilling operations and hence fall short of 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Suyi Jiang , Haimin Luo , Haoran Jiang , Ziyu Wang , Jingyi Yu , Lan Xu

Recent advances in generative AI have unveiled significant potential for the creation of 3D content. However, current methods either apply a pre-trained 2D diffusion model with the time-consuming score distillation sampling (SDS), or a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yuanxun Lu , Jingyang Zhang , Shiwei Li , Tian Fang , David McKinnon , Yanghai Tsin , Long Quan , Xun Cao , Yao Yao

This paper tackles the problem of generalizable 3D-aware generation from monocular datasets, e.g., ImageNet. The key challenge of this task is learning a robust 3D-aware representation without multi-view or dynamic data, while ensuring…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Yuxin Wang , Qianyi Wu , Dan Xu

Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Canxuan Gang

Recent advances in text-to-image diffusion models have been driven by the increasing availability of paired 2D data. However, the development of 3D diffusion models has been hindered by the scarcity of high-quality 3D data, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Tiange Xiang , Kai Li , Chengjiang Long , Christian Häne , Peihong Guo , Scott Delp , Ehsan Adeli , Li Fei-Fei

Text-to-3D generation has recently garnered significant attention, fueled by 2D diffusion models trained on billions of image-text pairs. Existing methods primarily rely on score distillation to leverage the 2D diffusion priors to supervise…

Computer Vision and Pattern Recognition · Computer Science 2023-07-27 Chaohui Yu , Qiang Zhou , Jingliang Li , Zhe Zhang , Zhibin Wang , Fan Wang

Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However, most existing works focus solely on the direct generation, ignoring the editing, restricting them from synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Yunjie Wu , Yapeng Meng , Zhipeng Hu , Lincheng Li , Haoqian Wu , Kun Zhou , Weiwei Xu , Xin Yu

Recently, 3D generation methods have shown their powerful ability to automate 3D model creation. However, most 3D generation methods only rely on an input image or a text prompt to generate a 3D model, which lacks the control of each…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Peng Li , Suizhi Ma , Jialiang Chen , Yuan Liu , Congyi Zhang , Wei Xue , Wenhan Luo , Alla Sheffer , Wenping Wang , Yike Guo

This work presents a novel text-to-vector graphics generation approach, Dream3DVG, allowing for arbitrary viewpoint viewing, progressive detail optimization, and view-dependent occlusion awareness. Our approach is a dual-branch optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Yidi Li , Jun Xiao , Zhengda Lu , Yiqun Wang , Haiyong Jiang

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions. However, relying solely on text for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Pu Cao , Feng Zhou , Qing Song , Lu Yang

Existing text-based 3D generation methods generate attractive results but lack detailed geometry control. Sketches, known for their conciseness and expressiveness, have contributed to intuitive 3D modeling but are confined to producing…

Graphics · Computer Science 2024-05-15 Feng-Lin Liu , Hongbo Fu , Yu-Kun Lai , Lin Gao

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

Text-to-3D is an emerging task that allows users to create 3D content with infinite possibilities. Existing works tackle the problem by optimizing a 3D representation with guidance from pre-trained diffusion models. An apparent drawback is…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Yiji Cheng , Fei Yin , Xiaoke Huang , Xintong Yu , Jiaxiang Liu , Shikun Feng , Yujiu Yang , Yansong Tang

Text-guided domain adaptation and generation of 3D-aware portraits find many applications in various fields. However, due to the lack of training data and the challenges in handling the high variety of geometry and appearance, the existing…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Biwen Lei , Kai Yu , Mengyang Feng , Miaomiao Cui , Xuansong Xie

Autonomous driving systems rely heavily on multimodal perception data to understand complex environments. However, the long-tailed distribution of real-world data hinders generalization, especially for rare but safety-critical vehicle…

Artificial Intelligence · Computer Science 2025-08-01 Shouyi Lu , Zihan Lin , Chao Lu , Huanran Wang , Guirong Zhuo , Lianqing Zheng

Novel-view synthesis aims to generate novel views of a scene from multiple input images or videos, and recent advancements like 3D Gaussian splatting (3DGS) have achieved notable success in producing photorealistic renderings with efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Xi Liu , Chaoyi Zhou , Siyu Huang