Search Results for author:
Found 24 papers, 15 papers with code
DiffSF: Diffusion Models for Scene Flow Estimation
Aiming at improving accuracy while additionally providing an estimate for uncertainty, we propose DiffSF that combines transformer-based scene flow estimation with denoising diffusion models.
The voraus-AD Dataset for Anomaly Detection in Robot Applications
During the operation of industrial robots, unusual events may endanger the safety of humans and the quality of production.
Ranked #1 on
Anomaly Detection
on voraus-AD
Mirror-Aware Neural Humans
Human motion capture either requires multi-camera systems or is unreliable using single-view input due to depth ambiguities.
Pose Modulated Avatars from Video
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.
Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks
Computer vision systems that are deployed in safety-critical applications need to quantify their output uncertainty.
DiffPose: Multi-hypothesis Human Pose Estimation using Diffusion models
Since such a simplification of the heatmaps removes valid information about possibly correct, though labeled unlikely, joint locations, we propose to represent the heatmaps as a set of 2D joint candidate samples.
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection
We train a normalizing flow for density estimation as a teacher and a conventional feed-forward network as a student to trigger large distances for anomalies: The bijectivity of the normalizing flow enforces a divergence of teacher outputs for anomalies compared to normal data.
Ranked #1 on
Anomaly Detection
on MVTEC 3D-AD
(Detection AUROC metric, using extra
training data)
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
Our key ingredients are i) an encoder that predicts keypoint locations in an input image, ii) a shared graph as a latent variable that links the same pairs of keypoints in every image, iii) an intermediate edge map that combines the latent graph edge weights and keypoint locations in a soft, differentiable manner, and iv) an inpainting objective on randomly masked images.
Ranked #1 on
Unsupervised Landmark Detection
on MAFL Unaligned
LatentKeypointGAN: Controlling Images via Latent Keypoints -- Extended Abstract
Generative adversarial networks (GANs) can now generate photo-realistic images.
Improved 2D Keypoint Detection in Out-of-Balance and Fall Situations -- combining input rotations and a kinematic model
Injury analysis may be one of the most beneficial applications of deep learning based human pose estimation.
AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation
To this end, we propose AdaptPose, an end-to-end framework that generates synthetic 3D human motions from a source dataset and uses them to fine-tune a 3D pose estimator.
ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses
Human pose estimation from single images is a challenging problem that is typically solved by supervised learning.
Ranked #1 on
Unsupervised 3D Human Pose Estimation
on Human3.6M
3D Human Pose Estimation
Unsupervised 3D Human Pose Estimation
+1
GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
Segmenting an image into its parts is a frequent preprocess for high-level vision tasks such as image editing.
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection
In industrial manufacturing processes, errors frequently occur at unpredictable times and in unknown manifestations.
Ranked #1 on
Anomaly Detection
on Surface Defect Saliency of Magnetic Tile
(using extra training data)
Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows
3D human pose estimation from monocular images is a highly ill-posed problem due to depth ambiguities and occlusions.
Ranked #46 on
3D Human Pose Estimation
on MPI-INF-3DHP
(PCK metric)
Monocular 3D Human Pose Estimation
Multi-Hypotheses 3D Human Pose Estimation
LatentKeypointGAN: Controlling GANs via Latent Keypoints
Generative adversarial networks (GANs) have attained photo-realistic quality in image generation.
Ranked #5 on
Unsupervised Keypoint Estimation
on CUB
AudioViewer: Learning to Visualize Sounds
Different from existing models that translate to hand sign language, between speech and text, or text and images, we target immediate and low-level audio to video translation that applies to generic environment sounds as well as human speech.
CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild
Human pose estimation from single images is a challenging problem in computer vision that requires large amounts of labeled training data to be solved accurately.
Ranked #3 on
3D Human Pose Estimation
on SkiPose
Monocular 3D Human Pose Estimation
Weakly-supervised 3D Human Pose Estimation
Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows
To achieve a high robustness and performance we exploit multiple transformations in training and evaluation.
Ranked #2 on
Anomaly Detection
on InsPLAD
Weakly-supervised Learning of Human Dynamics
This paper proposes a weakly-supervised learning framework for dynamics estimation from human motion.
RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation
This efficiently avoids a simple memorization of the training data and allows for a weakly supervised training.
Ranked #24 on
Weakly-supervised 3D Human Pose Estimation
on Human3.6M
A Kinematic Chain Space for Monocular Motion Capture
This paper deals with motion capture of kinematic chains (e. g. human skeletons) from monocular image sequences taken by uncalibrated cameras.
