604 citations · 1k across the 30 of their papers we have counts for
43 papers · 1 filter
SF2SE3: Clustering Scene Flow into SE(3)-Motions via Proposal and Selection
Leonhard Sommer, Philipp Schröppel, Thomas Brox
We propose SF2SE3, a novel approach to estimate scene dynamics in form of a segmentation into independently moving rigid objects and their SE(3)-motions. SF2SE3 operates on two con…
A Benchmark and a Baseline for Robust Multi-view Depth Estimation
Philipp Schröppel, Jan Bechtold, Artemij Amiranashvili +1
Recent deep learning approaches for multi-view depth estimation are employed either in a depth-from-video or a multi-view stereo setting. Despite different settings, these approach…
Neural Architecture Search for Dense Prediction Tasks in Computer Vision
Thomas Elsken, Arber Zela, Jan Hendrik Metzen +4
The success of deep learning in recent years has lead to a rising demand for neural network architecture engineering. As a consequence, neural architecture search (NAS), which aims…
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…
CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations
Mohammadreza Zolfaghari, Yi Zhu, Peter Gehler +1
Contrastive learning allows us to flexibly define powerful losses by contrasting positive pairs from sets of negative samples. Recently, the principle has also been used to learn c…
Contrastive Representation Learning for Hand Shape Estimation
Christian Zimmermann, Max Argus, Thomas Brox
This work presents improvements in monocular hand shape estimation by building on top of recent advances in unsupervised learning. We extend momentum contrastive learning and contr…