Holistic-Motion2D: Scalable Whole-body Human Motion Generation in 2D Space
Tsinghua University（清华大学）；The University of Sydney（悉尼大学）；Shanghai AI Laboratory（上海人工智能实验室）；The Chinese University of Hong Kong（香港中文大学）；Alibaba Group（阿里巴巴集团）；HKUST（香港科技大学）；Shandong University（山东大学）
In this paper, we introduce a novel path to $\textit{general}$ human motion generation by focusing on 2D space. Traditional methods have primarily generated human motions in 3D, which, while detailed and realistic, are often limited by the scope of available 3D motion data in terms of both the size and the diversity. To address these limitations, we exploit extensive availability of 2D motion data. We present $\textbf{Holistic-Motion2D}$, the first comprehensive and large-scale benchmark for 2D whole-body motion generation, which includes over 1M in-the-wild motion sequences, each paired with high-quality whole-body/partial pose annotations and textual descriptions. Notably, Holistic-Motion2D is ten times larger than the previously largest 3D motion dataset. We also introduce a baseline method, featuring innovative $\textit{whole-body part-aware attention}$ and $\textit{confidence-aware modeling}$ techniques, tailored for 2D $\underline{\text T}$ext-driv$\underline{\text{EN}}$ whole-bo$\underline{\text D}$y motion gen$\underline{\text{ER}}$ation, namely $\textbf{Tender}$. Extensive experiments demonstrate the effectiveness of $\textbf{Holistic-Motion2D}$ and $\textbf{Tender}$ in generating expressive, diverse, and realistic human motions. We also highlight the utility of 2D motion for various downstream applications and its potential for lifting to 3D motion. The page link is: https://holistic-motion2d.github.io.
International Digital Economy Academy (IDEA)（国际数字经济研究院（IDEA））；School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-SZ)（香港中文大学（深圳）数据科学学院）；Tsinghua University（清华大学）
RapVerse: Coherent Vocals and Whole-Body Motions Generations from Text
UMass Amherst（马萨诸塞大学阿默斯特分校）；Wuhan University（武汉大学）；UC San Diego（加州大学圣地亚哥分校）；Tsinghua University（清华大学）；MIT-IBM Watson AI Lab（麻省理工-IBM沃森人工智能实验室）；Dolby Laboratories（杜比实验室）
LSP-DETR: Efficient and Scalable Nuclei Segmentation in Whole-Slide Images
Masaryk University, Faculty of Informatics（马萨里克大学信息学院）；Masaryk University, Institute for Computer Science（马萨里克大学计算机科学研究所）；Masaryk Memorial Cancer Institute（马萨里克纪念癌症研究所）
Scalable Trajectory Generation for Whole-Body Mobile Manipulation
Institute for AI, Peking University（人工智能研究院，北京大学）；Institute of Unmanned System, Beihang University（无人系统研究院，北航）；School of Psychological and Cognitive Sciences, Peking University（心理学与认知科学学院，北京大学）；State Key Laboratory of General Artificial Intelligence（通用人工智能国家重点实验室）；Beijing Key Laboratory of Behavior and Mental Health, Peking University（北京行为与心理健康重点实验室，北京大学）；Yuanpei College, Peking University（元培学院，北京大学）；Embodied Intelligence Lab, PKU-Wuhan Institute for Artificial Intelligence（具身智能实验室，PKU-武汉人工智能研究所）
Bring Your Own Character: A Holistic Solution for Automatic Facial Animation Generation of Customized Characters
Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所）；National University of Singapore（新加坡国立大学）；University of Chinese Academy of Sciences（中国科学院大学）
本文提出一种自动生成定制虚拟人面部动画的整体方案，通过深度学习估计 blendshape 系数实现表情重定向，并开发 Unity 3D 工具包结合人在回路反馈优化，以加速 VR 面部动画生成。
Scalable, Trustworthy Generative Model for Virtual Multi-Staining from H&E Whole Slide Images
Sorbonne Université（索邦大学）；CNRS（法国国家科学研究中心）；Inserm（法国国家健康与医学研究院）；AP-HP（巴黎公共医疗集团）；Inria（法国国家信息与自动化研究所）；Paris Brain Institute-ICM（巴黎大脑研究所-脑研究所）；Paris Cité University（巴黎城市大学）；Necker-Enfants Malades University Hospitals（内克尔-儿童马尔代夫大学医院）；Centre de recherche sur l’inflammation（炎症研究中心）；Robert Debré University Hospitals（罗伯特德布雷大学医院）
