5 citations · 8 across the 5 of their papers we have counts for
5 papers
JEPADepth: Masked Predictive Representation Learning for Self-Supervised Monocular Depth Estimation
Ionuţ Grigore, Călin-Adrian Popa
Self-supervised monocular depth estimation typically relies on photometric reconstruction losses that couple depth, pose, and appearance assumptions. In this paper, we propose JEPA…
FPC-Net: Revisiting SuperPoint with Descriptor-Free Keypoint Detection via Feature Pyramids and Consistency-Based Implicit Matching
Ionuţ Grigore, Călin-Adrian Popa, Claudiu Leoveanu-Condrei
The extraction and matching of interest points are fundamental to many geometric computer vision tasks. Traditionally, matching is performed by assigning descriptors to interest po…
MambaDepth: Enhancing Long-range Dependency for Self-Supervised Fine-Structured Monocular Depth Estimation
Ionuţ Grigore, Călin-Adrian Popa
In the field of self-supervised depth estimation, Convolutional Neural Networks (CNNs) and Transformers have traditionally been dominant. However, both architectures struggle with…
XAMI -- A Benchmark Dataset for Artefact Detection in XMM-Newton Optical Images
Julia Dima, Pablo Gómez, Sandor Kruk +3
Reflected or scattered light produce artefacts in astronomical observations that can negatively impact the scientific study. Hence, automated detection of these artefacts is highly…
Averaging on Manifolds by Embedding Algorithm
Petre Birtea, Dan Comănescu, Călin-Adrian Popa
We will propose a new algorithm for finding critical points of cost functions defined on a differential manifold. We will lift the initial cost function to a manifold that can be e…