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The advancements in automatic text-to-3D generation have been remarkable. Most existing methods use pre-trained text-to-image diffusion models to optimize 3D representations like Neural Radiance Fields (NeRFs) via latent-space denoising…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Junzhe Zhu , Peiye Zhuang , Sanmi Koyejo

With the growing popularity of personalized human content creation and sharing, there is a rising demand for advanced techniques in customized human image generation. However, current methods struggle to simultaneously maintain the fidelity…

Graphics · Computer Science 2025-02-21 Ye Wang , Xuping Xie , Lanjun Wang , Zili Yi , Rui Ma

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

Creating high-fidelity, animatable 3D talking heads is crucial for immersive applications, yet often hindered by the prevalence of low-quality image or video sources, which yield poor 3D reconstructions. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Ding-Jiun Huang , Yuanhao Wang , Shao-Ji Yuan , Albert Mosella-Montoro , Francisco Vicente Carrasco , Cheng Zhang , Fernando De la Torre

With recent advancements in neural rendering and motion capture algorithms, remarkable progress has been made in photorealistic human avatar modeling, unlocking immense potential for applications in virtual reality, augmented reality,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Hendrik Junkawitsch , Guoxing Sun , Heming Zhu , Christian Theobalt , Marc Habermann

Recent years have seen an explosion of work and interest in text-to-3D shape generation. Much of the progress is driven by advances in 3D representations, large-scale pretraining and representation learning for text and image data enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Han-Hung Lee , Manolis Savva , Angel X. Chang

The diversity, quantity, and quality of manipulation data are critical for training effective robot policies. However, due to hardware and physical setup constraints, collecting large-scale real-world manipulation data remains difficult to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Boyang Wang , Haoran Zhang , Shujie Zhang , Jinkun Hao , Mingda Jia , Qi Lv , Yucheng Mao , Zhaoyang Lyu , Jia Zeng , Xudong Xu , Jiangmiao Pang

Recent advancements in 3D avatar generation excel with multi-view supervision for photorealistic models. However, monocular counterparts lag in quality despite broader applicability. We propose ReCaLaB to close this gap. ReCaLaB is a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Yuchen Rao , Eduardo Perez Pellitero , Benjamin Busam , Yiren Zhou , Jifei Song

The realism of digital avatars is crucial in enabling telepresence applications with self-expression and customization. While physical simulations can produce realistic motions for clothed humans, they require high-quality garment assets…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Yifei Li , Hsiao-yu Chen , Egor Larionov , Nikolaos Sarafianos , Wojciech Matusik , Tuur Stuyck

Reconstructing photorealistic and animatable 4D head avatars from a single portrait image remains a fundamental challenge in computer vision. While diffusion models have enabled remarkable progress in image and video generation for avatar…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Chao Xu , Xiaochen Zhao , Xiang Deng , Jingxiang Sun , Donglin Di , Zhuo Su , Yebin Liu

We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions. Our approach uses a 4D dynamic Neural Radiance Field (NeRF), which is optimized for scene appearance, density, and motion…

Computer Vision and Pattern Recognition · Computer Science 2023-01-27 Uriel Singer , Shelly Sheynin , Adam Polyak , Oron Ashual , Iurii Makarov , Filippos Kokkinos , Naman Goyal , Andrea Vedaldi , Devi Parikh , Justin Johnson , Yaniv Taigman

Stylized 3D avatars have become increasingly prominent in our modern life. Creating these avatars manually usually involves laborious selection and adjustment of continuous and discrete parameters and is time-consuming for average users.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-16 Shen Sang , Tiancheng Zhi , Guoxian Song , Minghao Liu , Chunpong Lai , Jing Liu , Xiang Wen , James Davis , Linjie Luo

Recent advancements in generative models have enabled the creation of dynamic 4D content - 3D objects in motion - based on text prompts, which holds potential for applications in virtual worlds, media, and gaming. Existing methods provide…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Ohad Rahamim , Ori Malca , Dvir Samuel , Gal Chechik

Inspired by the effectiveness of 3D Gaussian Splatting (3DGS) in reconstructing detailed 3D scenes within multi-view setups and the emergence of large 2D human foundation models, we introduce Arc2Avatar, the first SDS-based method utilizing…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Dimitrios Gerogiannis , Foivos Paraperas Papantoniou , Rolandos Alexandros Potamias , Alexandros Lattas , Stefanos Zafeiriou

There has been significant progress in generating an animatable 3D human avatar from a single image. However, recovering texture for the 3D human avatar from a single image has been relatively less addressed. Because the generated 3D human…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Sihun Cha , Kwanggyoon Seo , Amirsaman Ashtari , Junyong Noh

Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years. Although these image synthesis methods produce visually appealing results, they frequently exhibit spelling errors…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yiming Zhao , Zhouhui Lian

We present a framework for generating full-bodied photorealistic avatars that gesture according to the conversational dynamics of a dyadic interaction. Given speech audio, we output multiple possibilities of gestural motion for an…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Evonne Ng , Javier Romero , Timur Bagautdinov , Shaojie Bai , Trevor Darrell , Angjoo Kanazawa , Alexander Richard

In practical real-time XR and telepresence applications, network and computing resources fluctuate frequently. Therefore, a progressive 3D representation is needed. To this end, we propose ProgressiveAvatars, a progressive avatar…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Kaiwen Song , Jinkai Cui , Juyong Zhang

Recent advances in 3D generation have been remarkable, with methods such as DreamFusion leveraging large-scale text-to-image diffusion-based models to guide 3D object generation. These methods enable the synthesis of detailed and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Bohan Zeng , Shanglin Li , Yutang Feng , Ling Yang , Hong Li , Sicheng Gao , Jiaming Liu , Conghui He , Wentao Zhang , Jianzhuang Liu , Baochang Zhang , Shuicheng Yan

Existing single-image 3D human avatar methods primarily rely on rigid joint transformations, limiting their ability to model realistic cloth dynamics. We present DynaAvatar, a zero-shot framework that reconstructs animatable 3D human…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Joohyun Kwon , Geonhee Sim , Gyeongsik Moon