Massimiliano Mancini

Orcid: 0000-0001-8595-9955

According to our database1, Massimiliano Mancini authored at least 60 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Relational Proxies: Fine-Grained Relationships as Zero-Shot Discriminators.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Learning Graph Embeddings for Open World Compositional Zero-Shot Learning.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Semi-Supervised and Unsupervised Deep Visual Learning: A Survey.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

GradBias: Unveiling Word Influence on Bias in Text-to-Image Generative Models.
CoRR, 2024

The Phantom Menace: Unmasking Privacy Leakages in Vision-Language Models.
CoRR, 2024

One-Shot Unlearning of Personal Identities.
CoRR, 2024

Automatic benchmarking of large multimodal models via iterative experiment programming.
CoRR, 2024

Frustratingly Easy Test-Time Adaptation of Vision-Language Models.
CoRR, 2024

Less is more: Summarizing Patch Tokens for efficient Multi-Label Class-Incremental Learning.
CoRR, 2024

Vocabulary-free Image Classification and Semantic Segmentation.
CoRR, 2024

MULTIFLOW: Shifting Towards Task-Agnostic Vision-Language Pruning.
CoRR, 2024

Vision-by-Language for Training-Free Compositional Image Retrieval.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Harnessing Large Language Models for Training-Free Video Anomaly Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

MULTIFLOW: Shifting Towards Task-Agnostic Vision-Language Pruning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

OpenBias: Open-Set Bias Detection in Text-to-Image Generative Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection.
CoRR, 2023

Vocabulary-free Image Classification.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

ProbVLM: Probabilistic Adapter for Frozen Vison-Language Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

PDiscoNet: Semantically consistent part discovery for fine-grained recognition.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Image-free Classifier Injection for Zero-Shot Classification.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Iterative Superquadric Recomposition of 3D Objects from Multiple Views.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Relational Proxies: Emergent Relationships as Fine-Grained Discriminators.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks.
Proceedings of the Computer Vision - ECCV 2022, 2022

Abstracting Sketches Through Simple Primitives.
Proceedings of the Computer Vision - ECCV 2022, 2022

KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Attention Consistency on Visual Corruptions for Single-Source Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image Retrieval.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
On the Challenges of Open World Recognition Under Shifting Visual Domains.
IEEE Robotics Autom. Lett., 2021

Inferring Latent Domains for Unsupervised Deep Domain Adaptation.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

On the Challenges of Open World Recognitionunder Shifting Visual Domains.
CoRR, 2021

Concurrent Discrimination and Alignment for Self-Supervised Feature Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

A Closer Look at Self-Training for Zero-Label Semantic Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Open World Compositional Zero-Shot Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Detecting Anomalies in Semantic Segmentation With Prototypes.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Cluster-Driven Graph Federated Learning Over Multiple Domains.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Prototype-based Incremental Few-Shot Segmentation.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Boosting Deep Open World Recognition by Clustering.
IEEE Robotics Autom. Lett., 2020

Boosting binary masks for multi-domain learning through affine transformations.
Mach. Vis. Appl., 2020

Towards Recognizing New Semantic Concepts in New Visual Domains.
CoRR, 2020

A Few Guidelines for Incremental Few-Shot Segmentation.
CoRR, 2020

Shape Consistent 2D Keypoint Estimation under Domain Shift.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Towards Recognizing Unseen Categories in Unseen Domains.
Proceedings of the Computer Vision - ECCV 2020, 2020

Modeling the Background for Incremental Learning in Semantic Segmentation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
The RGB-D Triathlon: Towards Agile Visual Toolboxes for Robots.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Knowledge is Never Enough: Towards Web Aided Deep Open World Recognition.
Proceedings of the International Conference on Robotics and Automation, 2019

Discovering Latent Domains for Unsupervised Domain Adaptation Through Consistency.
Proceedings of the Image Analysis and Processing - ICIAP 2019, 2019

AdaGraph: Unifying Predictive and Continuous Domain Adaptation Through Graphs.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Structured Domain Adaptation for 3D Keypoint Estimation.
Proceedings of the 2019 International Conference on 3D Vision, 2019

2018
Robust Place Categorization With Deep Domain Generalization.
IEEE Robotics Autom. Lett., 2018

Adding New Tasks to a Single Network with Weight Trasformations using Binary Masks.
CoRR, 2018

Kitting in the Wild through Online Domain Adaptation.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Best Sources Forward: Domain Generalization through Source-Specific Nets.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

Adding New Tasks to a Single Network with Weight Transformations Using Binary Masks.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Boosting Domain Adaptation by Discovering Latent Domains.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
Learning Deep NBNN Representations for Robust Place Categorization.
IEEE Robotics Autom. Lett., 2017

Inspiring Computer Vision System Solutions.
CoRR, 2017

Embedding Words and Senses Together via Joint Knowledge-Enhanced Training.
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017


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