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Niki Martinel

4 accepted papers

2026

Formally Exploring Visual Anomaly Detection Evaluation Metrics

ICML 2026poster

Inaccurate Visual Anomaly Detection (VAD) can lead to critical failures in safety-sensitive domains, including autonomous navigation and industrial surveillance. With the increasing abundance and rapid proliferation of VAD algorithms, their reliable evaluation has become increasingly important and c…

Cited by 0SourceScholar
2021

Weakly-Supervised Domain Adaptation of Deep Regression Trackers via Reinforced Knowledge Distillation

RA-L 2021

Deep regression trackers are among the fastest tracking algorithms available, and therefore suitable for real-time robotic applications. However, their accuracy is inadequate in many domains due to distribution shift and overfitting. In this letter we overcome such limitations by presenting the firs

Cited by 17SourceScholar
2017

Group Re-Identification via Unsupervised Transfer of Sparse Features Encoding

ICCV 2017poster

Person re-identification is best known as the problem of associating a single person that is observed from one or more disjoint cameras. The existing literature has mainly addressed such an issue, neglecting the fact that people usually move in groups, like in crowded scenarios. We believe that the…

Cited by 66PDFScholar
2015

Person Re-Identification Ranking Optimisation by Discriminant Context Information Analysis

ICCV 2015poster

Person re-identification is an open and challenging problem in computer vision. Existing re-identification approaches focus on optimal methods for features matching (e.g., metric learning approaches) or study the inter-camera transformations of such features. These methods hardly ever pay attention…

Cited by 131PDFScholar