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Related papers: Dual Diffusion Models for Multi-modal Guided 3D Av…

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We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encouraging results for text-to-3D generation of common objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Yukun Huang , Jianan Wang , Ailing Zeng , He Cao , Xianbiao Qi , Yukai Shi , Zheng-Jun Zha , Lei Zhang

Diffusion Transformer (DiT), an emerging diffusion model for visual generation, has demonstrated superior performance but suffers from substantial computational costs. Our investigations reveal that these costs primarily stem from the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Wangbo Zhao , Yizeng Han , Jiasheng Tang , Kai Wang , Hao Luo , Yibing Song , Gao Huang , Fan Wang , Yang You

Human video generation task has gained significant attention with the advancement of deep generative models. Generating realistic videos with human movements is challenging in nature, due to the intricacies of human body topology and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Zhangsihao Yang , Mengyi Shan , Mohammad Farazi , Wenhui Zhu , Yanxi Chen , Xuanzhao Dong , Yalin Wang

We present Make-A-Texture, a new framework that efficiently synthesizes high-resolution texture maps from textual prompts for given 3D geometries. Our approach progressively generates textures that are consistent across multiple viewpoints…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Xiaoyu Xiang , Liat Sless Gorelik , Yuchen Fan , Omri Armstrong , Forrest Iandola , Yilei Li , Ita Lifshitz , Rakesh Ranjan

Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability. This paper introduces a novel approach to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Zhixuan Yu , Ziqian Bai , Abhimitra Meka , Feitong Tan , Qiangeng Xu , Rohit Pandey , Sean Fanello , Hyun Soo Park , Yinda Zhang

Inpainting focuses on filling missing or corrupted regions of an image to blend seamlessly with its surrounding content and style. While conditional diffusion models have proven effective for text-guided inpainting, we introduce the novel…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Nicola Fanelli , Gennaro Vessio , Giovanna Castellano

Text-driven person image generation is an emerging and challenging task in cross-modality image generation. Controllable person image generation promotes a wide range of applications such as digital human interaction and virtual try-on.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-14 Kaiduo Zhang , Muyi Sun , Jianxin Sun , Binghao Zhao , Kunbo Zhang , Zhenan Sun , Tieniu Tan

Recent diffusion-based Single-image 3D portrait generation methods typically employ 2D diffusion models to provide multi-view knowledge, which is then distilled into 3D representations. However, these methods usually struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Haoran Wei , Wencheng Han , Xingping Dong , Jianbing Shen

Recent text-to-3D methods employing diffusion models have made significant advancements in 3D human generation. However, these approaches face challenges due to the limitations of text-to-image diffusion models, which lack an understanding…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xin Huang , Ruizhi Shao , Qi Zhang , Hongwen Zhang , Ying Feng , Yebin Liu , Qing Wang

Generating high-quality, photorealistic textures for 3D human avatars remains a fundamental yet challenging task in computer vision and multimedia field. However, real paired front and back images of human subjects are rarely available with…

Graphics · Computer Science 2026-04-10 Mingxiao Tu , Shuchang Ye , Hoijoon Jung , Jinman Kim

Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely on a pretrained text-guided image-to-image generative model…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Pengcheng Xu , Qingnan Fan , Fei Kou , Shuai Qin , Hong Gu , Ruoyu Zhao , Charles Ling , Boyu Wang

The text-to-image synthesis by diffusion models has recently shown remarkable performance in generating high-quality images. Although performs well for simple texts, the models may get confused when faced with complex texts that contain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Chang Yu , Junran Peng , Xiangyu Zhu , Zhaoxiang Zhang , Qi Tian , Zhen Lei

The issue of generative pretraining for vision models has persisted as a long-standing conundrum. At present, the text-to-image (T2I) diffusion model demonstrates remarkable proficiency in generating high-definition images matching textual…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Qiang Wan , Zilong Huang , Bingyi Kang , Jiashi Feng , Li Zhang

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. %…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Nikita Starodubcev , Dmitry Baranchuk , Valentin Khrulkov , Artem Babenko

Previous efforts have managed to generate production-ready 3D assets from text or images. However, these methods primarily employ NeRF or 3D Gaussian representations, which are not adept at producing smooth, high-quality geometries required…

Graphics · Computer Science 2024-10-15 Rengan Xie , Wenting Zheng , Kai Huang , Yizheng Chen , Qi Wang , Qi Ye , Wei Chen , Yuchi Huo

Diffusion models are emerging expressive generative models, in which a large number of time steps (inference steps) are required for a single image generation. To accelerate such tedious process, reducing steps uniformly is considered as an…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Lijiang Li , Huixia Li , Xiawu Zheng , Jie Wu , Xuefeng Xiao , Rui Wang , Min Zheng , Xin Pan , Fei Chao , Rongrong Ji

Speech-driven 3D facial animation plays a key role in applications such as virtual avatars, gaming, and digital content creation. While existing methods have made significant progress in achieving accurate lip synchronization and generating…

Graphics · Computer Science 2025-07-16 Yifang Pan , Karan Singh , Luiz Gustavo Hafemann

Face animation has achieved much progress in computer vision. However, prevailing GAN-based methods suffer from unnatural distortions and artifacts due to sophisticated motion deformation. In this paper, we propose a Face Animation…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Bohan Zeng , Xuhui Liu , Sicheng Gao , Boyu Liu , Hong Li , Jianzhuang Liu , Baochang Zhang

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

This paper presents a novel method to generate textures for 3D models given text prompts and 3D meshes. Additional depth information is taken into account to perform the Score Distillation Sampling (SDS) process with depth conditional…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Cindy Le , Congrui Hetang , Chendi Lin , Ang Cao , Yihui He