15 citations · 24 across the 13 of their papers we have counts for
8 papers · 1 filter
Inside Knowledge: Graph-based Path Generation with Explainable Data Augmentation and Curriculum Learning for Visual Indoor Navigation
Daniel Airinei, Elena Burceanu, Marius Leordeanu
Indoor navigation is a difficult task, as it generally comes with poor GPS access, forcing solutions to rely on other sources of information. While significant progress continues t…
Robust Novelty Detection through Style-Conscious Feature Ranking
Stefan Smeu, Elena Burceanu, Emanuela Haller +1
Novelty detection seeks to identify samples deviating from a known distribution, yet data shifts in a multitude of ways, and only a few consist of relevant changes. Aligned with ou…
Learning a Fast 3D Spectral Approach to Object Segmentation and Tracking over Space and Time
Elena Burceanu, Marius Leordeanu
We pose video object segmentation as spectral graph clustering in space and time, with one graph node for each pixel and edges forming local space-time neighborhoods. We claim that…
Env-Aware Anomaly Detection: Ignore Style Changes, Stay True to Content!
Stefan Smeu, Elena Burceanu, Andrei Liviu Nicolicioiu +1
We introduce a formalization and benchmark for the unsupervised anomaly detection task in the distribution-shift scenario. Our work builds upon the iWildCam dataset, and, to the be…
SFTrack++: A Fast Learnable Spectral Segmentation Approach for Space-Time Consistent Tracking
Elena Burceanu
We propose an object tracking method, SFTrack++, that smoothly learns to preserve the tracked object consistency over space and time dimensions by taking a spectral clustering appr…
A 3D Convolutional Approach to Spectral Object Segmentation in Space and Time
Elena Burceanu, Marius Leordeanu
We formulate object segmentation in video as a graph partitioning problem in space and time, in which nodes are pixels and their relations form local neighborhoods. We claim that t…
Learning a Robust Society of Tracking Parts using Co-occurrence Constraints
Elena Burceanu, Marius Leordeanu
Object tracking is an essential problem in computer vision that has been researched for several decades. One of the main challenges in tracking is to adapt to object appearance cha…
Learning a Robust Society of Tracking Parts
Elena Burceanu, Marius Leordeanu
Object tracking is an essential task in computer vision that has been studied since the early days of the field. Being able to follow objects that undergo different transformations…