Ismail Elezi

CoRR, 2024

V<sub>k</sub>D: Improving Knowledge Distillation using Orthogonal Projections.

[BibT_eX]

[DOI]

Roy Miles

CoRR, 2024

G3DR: Generative 3D Reconstruction in ImageNet.

[BibT_eX]

[DOI]

Pradyumna Reddy

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

$V_{k}D$: Improving Knowledge Distillation Using Orthogonal Projections.

[BibT_eX]

[DOI]

Roy Miles

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Three Heads Are Better than One: Complementary Experts for Long-Tailed Semi-supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

The Group Loss++: A Deeper Look Into Group Loss for Deep Metric Learning.

[BibT_eX]

[DOI]

Alessandro Torcinovich

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis.

[BibT_eX]

[DOI]

Cristian Canton-Ferrer

CoRR, 2023

Simple Cues Lead to a Strong Multi-Object Tracker.

[BibT_eX]

[DOI]

Jenny Seidenschwarz

Guillem Brasó

Victor Castro Serrano

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Simple Cues Lead to a Strong Multi-Object Tracker.

[BibT_eX]

[DOI]

CoRR, 2022

Learning to Discover and Detect Objects.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Decoupling Identity and Visual Quality for Image and Video Anonymization.

[BibT_eX]

[DOI]

Maxim Maximov

Jenny Denise Seidenschwarz

Proceedings of the Computer Vision - ACCV 2022, 2022

2021

Towards Reducing Labeling Cost in Deep Object Detection.

[BibT_eX]

[DOI]

CoRR, 2021

The 2021 Image Similarity Dataset and Challenge.

[BibT_eX]

[DOI]

Cristian Canton-Ferrer

CoRR, 2021

Learning Intra-Batch Connections for Deep Metric Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Active Learning for Deep Object Detection via Probabilistic Modeling.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Exploiting Contextual Information with Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

The Group Loss for Deep Metric Learning.

[BibT_eX]

[DOI]

Sebastiano Vascon

Alessandro Torcinovich

Proceedings of the Computer Vision - ECCV 2020, 2020

CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks.

[BibT_eX]

[DOI]

Maxim Maximov

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2018

DeepScores and Deep Watershed Detection: current state and open issues.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Watershed Detector for Music Object Recognition.

[BibT_eX]

[DOI]

Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018

DeepScores-A Dataset for Segmentation, Detection and Classification of Tiny Objects.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Transductive Label Augmentation for Improved Deep Network Learning.

[BibT_eX]

[DOI]

Alessandro Torcinovich

Sebastiano Vascon

Gilbert François Duivesteijn

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Deep Learning in the Wild.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks in Pattern Recognition, 2018

Learning Neural Models for End-to-End Clustering.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks in Pattern Recognition, 2018

2017

Revealing structure in large graphs: Szemerédi's regularity lemma and its use in pattern recognition.

[BibT_eX]

[DOI]