3 papers
cs.CV2025
Towards Sharper Object Boundaries in Self-Supervised Depth Estimation
Aurélien Cecille, Stefan Duffner, Franck Davoine +2
Accurate monocular depth estimation is crucial for 3D scene understanding, but existing methods often blur depth at object boundaries, introducing spurious intermediate 3D points.…
cs.CV2024
GroCo: Ground Constraint for Metric Self-Supervised Monocular Depth
Aurélien Cecille, Stefan Duffner, Franck Davoine +2
Monocular depth estimation has greatly improved in the recent years but models predicting metric depth still struggle to generalize across diverse camera poses and datasets. While…
cs.LG2024
On GNN explanability with activation rules
Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner +2
GNNs are powerful models based on node representation learning that perform particularly well in many machine learning problems related to graphs. The major obstacle to the deploym…