3D pose estimation
View article: PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes Open
Estimating the 6D pose of known objects is important for robots to interact with the real world.The problem is challenging due to the variety of objects as well as the complexity of a scene caused by clutter and occlusions between objects.…
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Exploiting Spatial-Temporal Relationships for 3D Pose Estimation via Graph Convolutional Networks Open
Despite great progress in 3D pose estimation from single-view images or videos, it remains a challenging task due to the substantial depth ambiguity and severe selfocclusions. Motivated by the effectiveness of incorporating spatial depende…
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Learning Pose Grammar to Encode Human Body Configuration for 3D Pose Estimation Open
In this paper, we propose a pose grammar to tackle the problem of 3D human pose estimation. Our model directly takes 2D pose as input and learns a generalized 2D-3D mapping function. The proposed model consists of a base network which effi…
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Deep 3D human pose estimation: A review Open
Three-dimensional (3D) human pose estimation involves estimating the articulated 3D joint locations of a human body from an image or video. Due to its widespread applications in a great variety of areas, such as human motion analysis, huma…
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Recognizing Human Actions as the Evolution of Pose Estimation Maps Open
Most video-based action recognition approaches choose to extract features from the whole video to recognize actions. The cluttered background and non-action motions limit the performances of these methods, since they lack the explicit mode…
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Segmentation-Driven 6D Object Pose Estimation Open
The most recent trend in estimating the 6D pose of rigid objects has been to train deep networks to either directly regress the pose from the image or to predict the 2D locations of 3D keypoints, from which the pose can be obtained using a…
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LCR-Net: Localization-Classification-Regression for Human Pose Open
International audience
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LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images Open
We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images. Key to our approach is the generation and scoring of a number of pose proposals per image, which allows us to predict 2D and 3D poses of mul…
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Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation Open
CVLAB
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Human Pose Regression by Combining Indirect Part Detection and\n Contextual Information Open
In this paper, we propose an end-to-end trainable regression approach for\nhuman pose estimation from still images. We use the proposed Soft-argmax\nfunction to convert feature maps directly to joint coordinates, resulting in a\nfully diff…
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Single-Stage 6D Object Pose Estimation Open
Most recent 6D pose estimation frameworks first rely on a deep network to establish correspondences between 3D object keypoints and 2D image locations and then use a variant of a RANSAC-based Perspective-n-Point (PnP) algorithm. This two-s…
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MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild Open
This paper addresses the problem of 3D human pose estimation in the wild. A significant challenge is the lack of training data, i.e., 2D images of humans annotated with 3D poses. Such data is necessary to train state-of-the-art CNN archite…
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Human Pose Estimation Using MediaPipe Pose and Optimization Method Based on a Humanoid Model Open
Seniors who live alone at home are at risk of falling and injuring themselves and, thus, may need a mobile robot that monitors and recognizes their poses automatically. Even though deep learning methods are actively evolving in this area, …
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Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images Open
International audience
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A Survey on Hand Pose Estimation with Wearable Sensors and Computer-Vision-Based Methods Open
Real-time sensing and modeling of the human body, especially the hands, is an important research endeavor for various applicative purposes such as in natural human computer interactions. Hand pose estimation is a big academic and technical…
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SHPR-Net: Deep Semantic Hand Pose Regression From Point Clouds Open
3-D hand pose estimation is an essential problem for human-computer interaction. Most of the existing depth-based hand pose estimation methods consume 2-D depth map or 3-D volume via 2-D/3-D convolutional neural networks. In this paper, we…
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Wide-Depth-Range 6D Object Pose Estimation in Space Open
6D pose estimation in space poses unique challenges that are not commonly encountered in the terrestrial setting. One of the most striking differences is the lack of atmospheric scattering, allowing objects to be visible from a great dista…
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A Review of Solutions for Perspective-n-Point Problem in Camera Pose Estimation Open
As there is a rapid development of robotics in the field of automation engineering, ego-motion estimation has become a most challenging task. In this review, we presented a model to help describe the PnP problems, and introduced two most c…
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Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks Open
In this paper, we present a novel method for real-time 3D hand pose estimation from single depth images using 3D Convolutional Neural Networks (CNNs). Image-based features extracted by 2D CNNs are not directly suitable for 3D hand pose est…
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A simple yet effective baseline for 3d human pose estimation Open
Following the success of deep convolutional networks, state-of-the-art methods for 3d human pose estimation have focused on deep end-to-end systems that predict 3d joint locations given raw image pixels. Despite their excellent performance…
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DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion Open
A key technical challenge in performing 6D object pose estimation from RGB-D image is to fully leverage the two complementary data sources. Prior works either extract information from the RGB image and depth separately or use costly post-p…
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A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape,\n Appearance, and Pose Open
While deep learning reshaped the classical motion capture pipeline with\nfeed-forward networks, generative models are required to recover fine alignment\nvia iterative refinement. Unfortunately, the existing models are usually\nhand-crafte…
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Model-based Deep Hand Pose Estimation Open
Previous learning based hand pose estimation methods does not fully exploit the prior information in hand model geometry. Instead, they usually rely a separate model fitting step to generate valid hand poses. Such a post processing is inco…
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Robust 3D Hand Pose Estimation From Single Depth Images Using Multi-View CNNs Open
Articulated hand pose estimation is one of core technologies in human-computer interaction. Despite the recent progress, most existing methods still cannot achieve satisfactory performance, partly due to the difficulty of the embedded high…
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Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions Open
Head-pose estimation has many applications, such as social event analysis, human-robot and human-computer interaction, driving assistance, and so forth. Head-pose estimation is challenging, because it must cope with changing illumination c…
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Learning Monocular 3D Human Pose Estimation from Multi-view Images Open
Accurate 3D human pose estimation from single images is possible with sophisticated deep-net architectures that have been trained on very large datasets. However, this still leaves open the problem of capturing motions for which no such da…
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A Comprehensive Review on 3D Object Detection and 6D Pose Estimation With Deep Learning Open
Nowadays, computer vision with 3D (dimension) object detection and 6D (degree of freedom) pose assumptions are widely discussed and studied in the field. In the 3D object detection process, classifications are centered on the object's size…
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Robust 3D Object Tracking from Monocular Images Using Stable Parts Open
We present an algorithm for estimating the pose of a rigid object in real-time under challenging conditions. Our method effectively handles poorly textured objects in cluttered, changing environments, even when their appearance is corrupte…
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Point Cloud Based Relative Pose Estimation of a Satellite in Close Range Open
Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estim…
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Adaptive Multi-View and Temporal Fusing Transformer for 3D Human Pose Estimation Open
This article proposes a unified framework dubbed Multi-view and Temporal Fusing Transformer (MTF-Transformer) to adaptively handle varying view numbers and video length without camera calibration in 3D Human Pose Estimation (HPE). It consi…