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Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical process of image formation. By inverting such renderer, one can think of a learning approach to infer 3D information from 2D images. However, standard…

Computer Vision and Pattern Recognition · Computer Science 2019-04-04 Shichen Liu , Tianye Li , Weikai Chen , Hao Li

There are a number of ways to procedurally generate interesting three-dimensional shapes, and a method where a cellular neural network is combined with a mesh growth algorithm is presented here. The aim is to create a shape from a genetic…

Neural and Evolutionary Computing · Computer Science 2016-03-30 Hugo Martay

Simulation is crucial for developing and evaluating autonomous vehicle (AV) systems. Recent literature builds on a new generation of generative models to synthesize highly realistic images for full-stack simulation. However, purely…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Zehao Zhu , Yuliang Zou , Chiyu Max Jiang , Bo Sun , Vincent Casser , Xiukun Huang , Jiahao Wang , Zhenpei Yang , Ruiqi Gao , Leonidas Guibas , Mingxing Tan , Dragomir Anguelov

The recent work of Gatys et al., who characterized the style of an image by the statistics of convolutional neural network filters, ignited a renewed interest in the texture generation and image stylization problems. While their image…

Computer Vision and Pattern Recognition · Computer Science 2017-11-07 Dmitry Ulyanov , Andrea Vedaldi , Victor Lempitsky

Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise. To simplify this process, we introduce MatFuse, a unified approach that harnesses the generative power of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Giuseppe Vecchio , Renato Sortino , Simone Palazzo , Concetto Spampinato

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

Deep generative models allow for photorealistic image synthesis at high resolutions. But for many applications, this is not enough: content creation also needs to be controllable. While several recent works investigate how to disentangle…

Computer Vision and Pattern Recognition · Computer Science 2021-04-30 Michael Niemeyer , Andreas Geiger

We propose a unified Generative Adversarial Network (GAN) for controllable image-to-image translation, i.e., transferring an image from a source to a target domain guided by controllable structures. In addition to conditioning on a…

Computer Vision and Pattern Recognition · Computer Science 2020-10-28 Hao Tang , Hong Liu , Nicu Sebe

We propose a learning based method for generating new animations of a cartoon character given a few example images. Our method is designed to learn from a traditionally animated sequence, where each frame is drawn by an artist, and thus the…

Computer Vision and Pattern Recognition · Computer Science 2020-10-14 Omid Poursaeed , Vladimir G. Kim , Eli Shechtman , Jun Saito , Serge Belongie

The generation of triangle meshes from point clouds, i.e. meshing, is a core task in computer graphics and computer vision. Traditional techniques directly construct a surface mesh using local decision heuristics, while some recent methods…

Computer Vision and Pattern Recognition · Computer Science 2022-10-06 Mathias Vetsch , Sandro Lombardi , Marc Pollefeys , Martin R. Oswald

Recent 3D Gaussian Splatting (3DGS) GANs for human heads synthesize and render photorealistic 3D models in real-time and offer a vast variety in identity and appearance. However, controlling specific semantic attributes such as hair color…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Florian Barthel , Shalini De Mello , Koki Nagano , Wieland Morgenstern , Anna Hilsmann , Peter Eisert

We explore neural painters, a generative model for brushstrokes learned from a real non-differentiable and non-deterministic painting program. We show that when training an agent to "paint" images using brushstrokes, using a differentiable…

Computer Vision and Pattern Recognition · Computer Science 2019-04-23 Reiichiro Nakano

Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substantial progress, such token sequences inevitably reuse…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Jeonghwan Kim , Yushi Lan , Armando Fortes , Yongwei Chen , Xingang Pan

Recent advancements in generative models have unlocked the capabilities to render photo-realistic data in a controllable fashion. Trained on the real data, these generative models are capable of producing realistic samples with minimal to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Abhay Rawat , Shubham Dokania , Astitva Srivastava , Shuaib Ahmed , Haiwen Feng , Rahul Tallamraju

The generation of high-quality, animatable 3D head avatars from text has enormous potential in content creation applications such as games, movies, and embodied virtual assistants. Current text-to-3D generation methods typically combine…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Yiqian Wu , Malte Prinzler , Xiaogang Jin , Siyu Tang

We introduce a novel method for real-time animation control and generation on rigged models using natural language input. First, we embed a large language model (LLM) in Unity to output structured texts that can be parsed into diverse and…

We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars. Due to the wide variety of human identities, poses, and stochastic details, the generation of 3D human meshes has been a challenging…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Byungjun Kim , Patrick Kwon , Kwangho Lee , Myunggi Lee , Sookwan Han , Daesik Kim , Hanbyul Joo

3D Morphable Models (3DMMs) have played a pivotal role as a fundamental representation or initialization for 3D avatar animation and reconstruction. However, extending 3DMMs to hair remains challenging due to the difficulty of enforcing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Zidu Wang , Jiankuo Zhao , Miao Xu , Xiangyu Zhu , Zhen Lei

Compared with traditional design methods, generative design significantly attracts engineers in various disciplines. In thiswork, howto achieve the real-time generative design of optimized structures with various diversities and…

Computational Engineering, Finance, and Science · Computer Science 2024-01-23 Zongliang Du , Xinyu Ma , Wenyu Hao , Yuan Liang , Xiaoyu Zhang , Hongzhi Luo , Xu Guo

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D object and scene generation, they still fall short of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Xingyi Li , Yizheng Wu , Jun Cen , Juewen Peng , Kewei Wang , Ke Xian , Zhe Wang , Zhiguo Cao , Guosheng Lin
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