12 citations · 51 across the 32 of their papers we have counts for
31 papers · 1 filter
CQF-HMR: Continuous Quaternion Flows for Probabilistic 3D Human Mesh Recovery from a Single Image
Cuong Le, Bao-Long Tran, Pavlo Melnyk +3
Recovering 3D digital humans from a single 2D image is an ill-posed computer vision problem due to the loss of depth information. Probabilistic 3D human pose estimation compensates…
Gravity-guided Contact Dynamics Estimation from 3D Human Motions
Cuong Le, Urs Waldmann, Bastian Wandt +1
Ground contact forces acting on the human body, are crucial for biomechanics studies or sport performance analysis. Prior methods rely on force plates or pressure mats to collect g…
QuaMo: Quaternion Motions for Vision-based 3D Human Kinematics Capture
Cuong Le, Pavlo Melnyk, Urs Waldmann +2
Vision-based 3D human motion capture from videos remains a challenge in computer vision. Traditional 3D pose estimation approaches often ignore the temporal consistency between fra…
Flow Matching for Probabilistic Monocular 3D Human Pose Estimation
Cuong Le, Pavlo Melnyk, Bastian Wandt +1
Recovering 3D human poses from a monocular camera view is a highly ill-posed problem due to the depth ambiguity. Earlier studies on 3D human pose lifting from 2D often contain inco…
On the Role of Rotation Equivariance in Monocular 2D-to-3D Human Pose Lifting
Pavlo Melnyk, Cuong Le, Urs Waldmann +2
We consider monocular 3D human pose estimation (HPE), where the goal is to predict 3D human skeletal joints from a single 2D image, typically via 2D keypoint detection followed by…
Continuous Normalizing Flows for Uncertainty-Aware Human Pose Estimation
Shipeng Liu, Ziliang Xiong, Bastian Wandt +1
Human Pose Estimation (HPE) is increasingly important for applications like virtual reality and motion analysis, yet current methods struggle with balancing accuracy, computational…
Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh Recovery
Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn +1
Monocular 3D human pose and shape estimation is an inherently ill-posed problem due to depth ambiguities, occlusions, and truncations. Recent probabilistic approaches learn a distr…
Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos
Cuong Le, Viktor Johansson, Manon Kok +1
Human motion capture from monocular videos has made significant progress in recent years. However, modern approaches often produce temporal artifacts, e.g. in form of jittery motio…
Temporally-consistent 3D Reconstruction of Birds
Johannes Hägerlind, Jonas Hentati-Sundberg, Bastian Wandt
This paper deals with 3D reconstruction of seabirds which recently came into focus of environmental scientists as valuable bio-indicators for environmental change. Such 3D informat…
Representing Animatable Avatar via Factorized Neural Fields
Chunjin Song, Zhijie Wu, Bastian Wandt +2
For reconstructing high-fidelity human 3D models from monocular videos, it is crucial to maintain consistent large-scale body shapes along with finely matched subtle wrinkles. This…
CasCalib: Cascaded Calibration for Motion Capture from Sparse Unsynchronized Cameras
James Tang, Shashwat Suri, Daniel Ajisafe +2
It is now possible to estimate 3D human pose from monocular images with off-the-shelf 3D pose estimators. However, many practical applications require fine-grained absolute pose in…
DiffSF: Diffusion Models for Scene Flow Estimation
Yushan Zhang, Bastian Wandt, Maria Magnusson +1
Scene flow estimation is an essential ingredient for a variety of real-world applications, especially for autonomous agents, such as self-driving cars and robots. While recent scen…
Pose Modulated Avatars from Video
Chunjin Song, Bastian Wandt, Helge Rhodin
It is now possible to reconstruct dynamic human motion and shape from a sparse set of cameras using Neural Radiance Fields (NeRF) driven by an underlying skeleton. However, a chall…
Mirror-Aware Neural Humans
Daniel Ajisafe, James Tang, Shih-Yang Su +2
Human motion capture either requires multi-camera systems or is unreliable when using single-view input due to depth ambiguities. Meanwhile, mirrors are readily available in urban…
GMSF: Global Matching Scene Flow
Yushan Zhang, Johan Edstedt, Bastian Wandt +3
We tackle the task of scene flow estimation from point clouds. Given a source and a target point cloud, the objective is to estimate a translation from each point in the source poi…
DiffPose: Multi-hypothesis Human Pose Estimation using Diffusion models
Karl Holmquist, Bastian Wandt
Traditionally, monocular 3D human pose estimation employs a machine learning model to predict the most likely 3D pose for a given input image. However, a single image can be highly…
LatentKeypointGAN: Controlling Images via Latent Keypoints -- Extended Abstract
Xingzhe He, Bastian Wandt, Helge Rhodin
Generative adversarial networks (GANs) can now generate photo-realistic images. However, how to best control the image content remains an open challenge. We introduce LatentKeypoin…
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
Xingzhe He, Bastian Wandt, Helge Rhodin
Structured representations such as keypoints are widely used in pose transfer, conditional image generation, animation, and 3D reconstruction. However, their supervised learning re…
Improved 2D Keypoint Detection in Out-of-Balance and Fall Situations -- combining input rotations and a kinematic model
Michael Zwölfer, Dieter Heinrich, Kurt Schindelwig +4
Injury analysis may be one of the most beneficial applications of deep learning based human pose estimation. To facilitate further research on this topic, we provide an injury spec…
ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses
Bastian Wandt, James J. Little, Helge Rhodin
Human pose estimation from single images is a challenging problem that is typically solved by supervised learning. Unfortunately, labeled training data does not yet exist for many…
AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation
Mohsen Gholami, Bastian Wandt, Helge Rhodin +2
This paper addresses the problem of cross-dataset generalization of 3D human pose estimation models. Testing a pre-trained 3D pose estimator on a new dataset results in a major per…
GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
Xingzhe He, Bastian Wandt, Helge Rhodin
Segmenting an image into its parts is a frequent preprocess for high-level vision tasks such as image editing. However, annotating masks for supervised training is expensive. Weakl…
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn +1
In industrial manufacturing processes, errors frequently occur at unpredictable times and in unknown manifestations. We tackle the problem of automatic defect detection without req…
Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows
Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn +1
3D human pose estimation from monocular images is a highly ill-posed problem due to depth ambiguities and occlusions. Nonetheless, most existing works ignore these ambiguities and…