2 citations · 7 across the 17 of their papers we have counts for
4 papers · 1 filter
Towards Learning Monocular 3D Object Localization From 2D Labels using the Physical Laws of Motion
Daniel Kienzle, Julian Lorenz, Katja Ludwig +1
We present a novel method for precise 3D object localization in single images from a single calibrated camera using only 2D labels. No expensive 3D labels are needed. Thus, instead…
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle +35
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Publ…
All Keypoints You Need: Detecting Arbitrary Keypoints on the Body of Triple, High, and Long Jump Athletes
Katja Ludwig, Julian Lorenz, Robin Schön +1
Performance analyses based on videos are commonly used by coaches of athletes in various sports disciplines. In individual sports, these analyses mainly comprise the body posture.…
Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidance
Robin Schön, Katja Ludwig, Rainer Lienhart
Pseudo depth maps are depth map predicitions which are used as ground truth during training. In this paper we leverage pseudo depth maps in order to segment objects of classes that…