32 citations · 35 across the 2 of their papers we have counts for
4 papers
Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives
David T. Hoffmann, Nadine Behrmann, Juergen Gall +2
This paper introduces Ranking Info Noise Contrastive Estimation (RINCE), a new member in the family of InfoNCE losses that preserves a ranked ordering of positive samples. In contr…
AGORA: Avatars in Geography Optimized for Regression Analysis
Priyanka Patel, Chun-Hao P. Huang, Joachim Tesch +3
While the accuracy of 3D human pose estimation from images has steadily improved on benchmark datasets, the best methods still fail in many real-world scenarios. This suggests that…
Learning Multi-Human Optical Flow
Anurag Ranjan, David T. Hoffmann, Dimitrios Tzionas +3
The optical flow of humans is well known to be useful for the analysis of human action. Recent optical flow methods focus on training deep networks to approach the problem. However…
Learning to Train with Synthetic Humans
David T. Hoffmann, Dimitrios Tzionas, Micheal J. Black +1
Neural networks need big annotated datasets for training. However, manual annotation can be too expensive or even unfeasible for certain tasks, like multi-person 2D pose estimation…