Fast and accurate real-time 3D hand-object pose estimation is generally recognized as a challenging scenario, specifically in the absence of depth-sensing cameras, high-performance computing and storage hardware. We propose a new lightweight, fast and accurate model for 3D hand object pose ...
《HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation》 本文提出了轻量HOPE-Net模型,用于在真实2D或3D情况下进行 手-物体姿态识别。 效果图如下: HOPE-Net采用了两个自适应级联的图卷积网络,一个在2D坐标下去估计手部关节点和物体,另一个图卷积网络将2D坐标转换为3D坐标。 本文提出的网络在2D和...
Estimating the 3D pose of a hand interacting with an object is a challenging task, harder than hand-only pose estimation as the object can cause heavy occlusion on the hand. We present a two stage discriminative approach using convolutional neural networks (CNN). The first stage classifies and...
Harmonious Feature Learning for Interactive Hand-Object Pose Estimation Zhifeng Lin1 Changxing Ding1,2* Huan Yao1 Zengsheng Kuang1 Shaoli Huang3 1 South China University of Technology 2 Pazhou Lab, Guangzhou 3 Tencent AI-Lab, Shenzhen eezhifenglin@mail.scut.edu....
The goal of Hand-Object Pose Estimation (HOPE) is to jointly estimate the poses of both the hand and a handled object. Our HOPE-Net model can estimate the 2D and 3D hand and object poses in real-time, given a single image. Architecture ...
HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields by Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis, EPFL (Switzerland). Overview We show that HOISDF achieves state-of-the-art results on hand-object pose estimation benchmarks (DexYCB and HO3Dv2)...
Table 1: The table shows the recent datasets with egocentric data for hand pose estimation.’S/R’: Synthetic or Real dataset. ’HOI’: Contains hand-object interaction data. Parse references Dataset S/R HOI Frames UCI-EGO[22] Real None 400 SynthHands[19] Synth both 63,530 EgoDexter[19...
Object Detection and Hand Pose Estimation with Python 链接: https://pan.baidu.com/s/1Erqt3mSpw5gXt1wbayt58A?pwd=8zr9 提取码: 8zr9 复制这段内容后打开百度网盘手机App,操作更方便哦 --来自百度网盘超级会员v7的分享 ANSYS生物力学仿真教程(workbench) ...
1)用触觉传感器的不变表示来捕捉手指与物体的接触面;2)用网络结构来融合视觉和触觉数据,以估计严重遮挡下的在手物体的6D姿势;3)产生适合在手物体6D姿势估计的合成视觉触觉数据集的方法。我们提出的实验结果表明,我们的模型在拟议的合成视觉触觉数据集上训练后,优于只使用同一数据集的颜色和深度图像训练的基线模型。
checkpoints config config_eval docs script thirdparty train .gitignore README.md environment.yml requirements.txt setup.py Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis CVPR, 2022 Lixin Yang *.Kailin Li *·Xinyu Zhan·Jun Lv·Wenqiang Xu·Jiefeng Li·Cewu...