April 12, 2023

Paper for L3D-IVU @ CVPR 2023 accepted

A paper with the title "Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance" by Robin Schön, Katja Ludwig and Rainer Lienhart has been accepted to the  2nd Workshop on Learning with Limited Labelled Data for Image and Video Understanding at the CVPR 2023. In this paper, the authors examine the effect of pseudo depth maps on the segmentation of object types which have not been present in the training data. The targeted objects are indicated by the means of coordinates on the object surfaces. In order to avoid a dependency ground truth depth maps, the depth maps are predicted by networks.
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Dieses Bild visualisiert die Segmentierung eines angeklickten Objekts auf Tiefenkarten.
April 5, 2023

Paper for CVSports @ CVPR 2023 accepted

The paper with the title "All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes" by Katja Ludwig, Julian Lorenz, Robin Schön and Rainer Lienhart is accepted at the 9th International Workshop on Computer Vision in Sports (CVsports) at CVPR 2023. In this paper, the authors detect arbitrary keypoints on the body of triple, high, and long jump athletes by extending previous methods with detections on the hands, feet, heads, elbows, and knees. Different representations regarding the head and the network input are evaluated in the paper.
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Example image from detection model showing body outline and intermediate lines
Nov. 29, 2022

Paper for CV4WS@WACV 2023 accepted

The paper with the title "Detecting Arbitrary Keypoints on Limbs and Skis with Sparse Partly Correct Segmentation Masks" from Katja Ludwig, Daniel Kienzle, Julian Lorenz and Rainer Lienhart is accepted for the workshop Computer Vision for Winter Sports on the IEEE/CVF Winter Conference on Applications in Computer Vision (WACV) 2023. In this paper, the authors describe how to detect arbitrary keypoints on the limbs and skis of ski jumpers. Only a few, partly correct segmentation masks are necessary in the dataset for the presented method.

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Prof. Dr. Rainer Lienhart

Lehrstuhl für Maschinelles Lernen und Maschinelles Sehen

Institut für Informatik

Universität Augsburg

Universitätsstr. 6a

D -       89159 Augsburg




+49 (821) 598-5703



rainer.lienhart @informatik.uni-



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