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Related papers: WildAvatar: Learning In-the-wild 3D Avatars from t…

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In recent years, there has been significant interest in creating 3D avatars and motions, driven by their diverse applications in areas like film-making, video games, AR/VR, and human-robot interaction. However, current efforts primarily…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Zeyu Zhang , Yiran Wang , Biao Wu , Shuo Chen , Zhiyuan Zhang , Shiya Huang , Wenbo Zhang , Meng Fang , Ling Chen , Yang Zhao

Video quality assessment (VQA) is an important problem in computer vision. The videos in computer vision applications are usually captured in the wild. We focus on automatically assessing the quality of in-the-wild videos, which is a…

Computer Vision and Pattern Recognition · Computer Science 2021-02-11 Dingquan Li , Tingting Jiang , Ming Jiang

Existing video understanding datasets mostly focus on human interactions, with little attention being paid to the "in the wild" settings, where the videos are recorded outdoors. We propose WILDQA, a video understanding dataset of videos…

Computer Vision and Pattern Recognition · Computer Science 2022-09-15 Santiago Castro , Naihao Deng , Pingxuan Huang , Mihai Burzo , Rada Mihalcea

We present a fully automatic approach to real-time 3D face reconstruction from monocular in-the-wild videos. With the use of a cascaded-regressor based face tracking and a 3D Morphable Face Model shape fitting, we obtain a semi-dense 3D…

Computer Vision and Pattern Recognition · Computer Science 2017-08-28 Patrik Huber , Philipp Kopp , Matthias Rätsch , William Christmas , Josef Kittler

The quality of the data and annotation upper-bounds the quality of a downstream model. While there exist large text corpora and image-text pairs, high-quality video-text data is much harder to collect. First of all, manual labeling is more…

Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details. Neural volumetric representations approach photorealism but are hard to animate and do not…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Yufeng Zheng , Victoria Fernández Abrevaya , Marcel C. Bühler , Xu Chen , Michael J. Black , Otmar Hilliges

Synthesizing high-quality 3D face models from natural language descriptions is very valuable for many applications, including avatar creation, virtual reality, and telepresence. However, little research ever tapped into this task. We argue…

Computer Vision and Pattern Recognition · Computer Science 2023-05-08 Menghua Wu , Hao Zhu , Linjia Huang , Yiyu Zhuang , Yuanxun Lu , Xun Cao

Recent advances in multimodal large language models have driven growing interest in graphical user interface (GUI) agents, yet their generalization remains constrained by the scarcity of large-scale training data spanning diverse real-world…

Computation and Language · Computer Science 2026-05-15 Weimin Xiong , Shuhao Gu , Bowen Ye , Zihao Yue , Lei Li , Feifan Song , Sujian Li , Hao Tian

Capturing the dynamically deforming 3D shape of clothed human is essential for numerous applications, including VR/AR, autonomous driving, and human-computer interaction. Existing methods either require a highly specialized capturing setup,…

Computer Vision and Pattern Recognition · Computer Science 2021-12-01 Chen Guo , Xu Chen , Jie Song , Otmar Hilliges

Numerous advancements in deep learning can be attributed to the access to large-scale and well-annotated datasets. However, such a dataset is prohibitively expensive in 3D computer vision due to the substantial collection cost. To alleviate…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Xinke Li , Henghui Ding , Zekun Tong , Yuwei Wu , Yeow Meng Chee

3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technology to a larger audience, we propose AvatarCLIP, a zero-shot…

Computer Vision and Pattern Recognition · Computer Science 2022-05-18 Fangzhou Hong , Mingyuan Zhang , Liang Pan , Zhongang Cai , Lei Yang , Ziwei Liu

We propose an end-to-end pipeline for both building and tracking 3D facial models from personalized in-the-wild (cellphone, webcam, youtube clips, etc.) video data. First, we present a method for automatic data curation and retrieval based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-28 Winnie Lin , Yilin Zhu , Demi Guo , Ron Fedkiw

With the booming of virtual reality (VR) technology, there is a growing need for customized 3D avatars. However, traditional methods for 3D avatar modeling are either time-consuming or fail to retain similarity to the person being modeled.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Chuanyu Pan , Guowei Yang , Taijiang Mu , Yu-Kun Lai

Creating 3D head avatars is a significant yet challenging task for many applicated scenarios. Previous studies have set out to learn 3D human head generative models using massive 2D image data. Although these models are highly generalizable…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Yiyu Zhuang , Yuxiao He , Jiawei Zhang , Yanwen Wang , Jiahe Zhu , Yao Yao , Siyu Zhu , Xun Cao , Hao Zhu

With the recent popularity of animated GIFs on social media, there is need for ways to index them with rich metadata. To advance research on animated GIF understanding, we collected a new dataset, Tumblr GIF (TGIF), with 100K animated GIFs…

Computer Vision and Pattern Recognition · Computer Science 2016-04-13 Yuncheng Li , Yale Song , Liangliang Cao , Joel Tetreault , Larry Goldberg , Alejandro Jaimes , Jiebo Luo

Recently, implicit neural representation has been widely used to generate animatable human avatars. However, the materials and geometry of those representations are coupled in the neural network and hard to edit, which hinders their…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Qifeng Chen , Rengan Xie , Kai Huang , Qi Wang , Wenting Zheng , Rong Li , Yuchi Huo

Applying Machine learning to domains like Earth Sciences is impeded by the lack of labeled data, despite a large corpus of raw data available in such domains. For instance, training a wildfire classifier on satellite imagery requires…

Computer Vision and Pattern Recognition · Computer Science 2023-01-02 Tarun Narayanan , Ajay Krishnan , Anirudh Koul , Siddha Ganju

Recent advances in Generative AI (GenAI) have led to significant improvements in the quality of generated visual content. As AI-generated visual content becomes increasingly indistinguishable from real content, the challenge of detecting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Keerthi Veeramachaneni , Praveen Tirupattur , Amrit Singh Bedi , Mubarak Shah

This paper presents an in-depth exploration of 3D human model and avatar generation technology, propelled by the rapid advancements in large-scale models and artificial intelligence. The paper reviews the comprehensive process of 3D human…

Graphics · Computer Science 2024-06-04 Lei Liu , Ke Zhao

Although much progress has been made in 3D clothed human reconstruction, most of the existing methods fail to produce robust results from in-the-wild images, which contain diverse human poses and appearances. This is mainly due to the large…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Gyeongsik Moon , Hyeongjin Nam , Takaaki Shiratori , Kyoung Mu Lee