30 citations · 41 across the 12 of their papers we have counts for
7 papers · 1 filter
Data Selection Through Iterative Self-Filtering for Vision-Language Settings
Andrei Liviu Nicolicioiu, Sarvjeet Singh Ghotra, Morgane M. Moss +1
The availability of large amounts of clean data is paramount to training neural networks. However, at large scales, manual oversight is impractical, resulting in sizeable datasets…
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 Diverse Features in Vision Transformers for Improved Generalization
Armand Mihai Nicolicioiu, Andrei Liviu Nicolicioiu, Bogdan Alexe +1
Deep learning models often rely only on a small set of features even when there is a rich set of predictive signals in the training data. This makes models brittle and sensitive to…
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…
Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural Networks
Iulia Duta, Andrei Nicolicioiu, Marius Leordeanu
Graph Neural Networks are perfectly suited to capture latent interactions between various entities in the spatio-temporal domain (e.g. videos). However, when an explicit structure…
Recurrent Space-time Graph Neural Networks
Andrei Nicolicioiu, Iulia Duta, Marius Leordeanu
Learning in the space-time domain remains a very challenging problem in machine learning and computer vision. Current computational models for understanding spatio-temporal visual…
Mining for meaning: from vision to language through multiple networks consensus
Iulia Duta, Andrei Liviu Nicolicioiu, Simion-Vlad Bogolin +1
Describing visual data into natural language is a very challenging task, at the intersection of computer vision, natural language processing and machine learning. Language goes wel…