Spatially-Variant Area Openings for Reference-Driven Adaptive Contour Preserving Filtering. - Gianni Franchi; Jesús Angulo (ICPR, 2014)

Comparative study on morphological principal component analysis of hyperspectral images. - Gianni Franchi; Jesús Angulo (WHISPERS, 2014)

Quantization of Hyperspectral Image Manifold Using Probabilistic Distances. - Gianni Franchi; Jesús Angulo (GSI, 2015)

Ordering on the Probability Simplex of Endmembers for Hyperspectral Morphological Image Processing. - Gianni Franchi; Jesús Angulo (ISMM, 2015)

Bagging Stochastic Watershed on Natural Color Image Segmentation. - Gianni Franchi; Jesús Angulo (ISMM, 2015)

A deep spatial/spectral descriptor of hyperspectral texture using scattering transform. - Gianni Franchi; Jesús Angulo (ICIP, 2016)

Hyperspectral image classification with support vector machines on kernel distribution embeddings. - Gianni Franchi; Jesús Angulo; Dino Sejdinovic (ICIP, 2016)

Morphological Principal Component Analysis for Hyperspectral Image Analysis. - Gianni Franchi; Jesús Angulo (ISPRS Int. J. Geo Inf., 2016)

Spatial machine learning applied to multivariate and multimodal images. (Machine learning spatial appliquée aux images multivariées et multimodales). - Gianni Franchi (2016)

Supervised Deep Kriging for Single-Image Super-Resolution. - Gianni Franchi; Angela Yao; Andreas Kolb 001 (GCPR, 2018)

Segmentation and Shape Extraction from Convolutional Neural Networks. - Mai Lan Ha; Gianni Franchi; Michael Möller 001; Andreas Kolb 001; Volker Blanz (WACV, 2018)

Crowd Behavior Characterization for Scene Tracking. - Gianni Franchi; Emanuel Aldea; Séverine Dubuisson; Isabelle Bloch (AVSS, 2019)

TRADI: Tracking Deep Neural Network Weight Distributions. - Gianni Franchi; Andrei Bursuc; Emanuel Aldea; Séverine Dubuisson; Isabelle Bloch (ECCV (17), 2020)

Tracking Hundreds of People in Densely Crowded Scenes With Particle Filtering Supervising Deep Convolutional Neural Networks. - Gianni Franchi; Emanuel Aldea; Séverine Dubuisson; Isabelle Bloch (ICIP, 2020)

One Versus all for deep Neural Network Incertitude (OVNNI) quantification. - Gianni Franchi; Andrei Bursuc; Emanuel Aldea; Séverine Dubuisson; Isabelle Bloch (CoRR, 2020)

Deep morphological networks. - Gianni Franchi; Amin Fehri; Angela Yao (Pattern Recognit., 2020)

Robust Semantic Segmentation with Superpixel-Mix. - Gianni Franchi; Nacim Belkhir; Mai Lan Ha; Yufei Hu; Andrei Bursuc; Volker Blanz; Angela Yao (BMVC, 2021)

SLURP: Side Learning Uncertainty for Regression Problems. - Xuanlong Yu; Gianni Franchi; Emanuel Aldea (BMVC, 2021)

EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case. - Natalia Díaz Rodríguez; Alberto Lamas 001; Jules Sanchez; Gianni Franchi; Ivan Donadello; Siham Tabik; David Filliat; Policarpo Cruz; Rosana Montes; Francisco Herrera (CoRR, 2021)

Learning a Discriminant Latent Space with Neural Discriminant Analysis. - Mai Lan Ha; Gianni Franchi; Emanuel Aldea; Volker Blanz (CoRR, 2021)

Reliable Semantic Segmentation with Superpixel-Mix. - Gianni Franchi; Nacim Belkhir; Mai Lan Ha; Yufei Hu; Andrei Bursuc; Volker Blanz; Angela Yao (CoRR, 2021)

MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks. - Gianni Franchi; Xuanlong Yu; Andrei Bursuc; Ángel Tena; Rémi Kazmierczak; Séverine Dubuisson; Emanuel Aldea; David Filliat (BMVC, 2022)

Latent Discriminant Deterministic Uncertainty. - Gianni Franchi; Xuanlong Yu; Andrei Bursuc; Emanuel Aldea; Séverine Dubuisson; David Filliat (ECCV (12), 2022)

On Monocular Depth Estimation and Uncertainty Quantification Using Classification Approaches for Regression. - Xuanlong Yu; Gianni Franchi; Emanuel Aldea (ICIP, 2022)

One Versus All for Deep Neural Network for Uncertainty (OVNNI) Quantification. - Gianni Franchi; Andrei Bursuc; Emanuel Aldea; Séverine Dubuisson; Isabelle Bloch (IEEE Access, 2022)

A study of deep perceptual metrics for image quality assessment. - Rémi Kazmierczak; Gianni Franchi; Nacim Belkhir; Antoine Manzanera; David Filliat (CoRR, 2022)

MUAD: Multiple Uncertainties for Autonomous Driving benchmark for multiple uncertainty types and tasks. - Gianni Franchi; Xuanlong Yu; Andrei Bursuc; Rémi Kazmierczak; Séverine Dubuisson; Emanuel Aldea; David Filliat (CoRR, 2022)

EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: The MonuMAI cultural heritage use case. - Natalia Díaz Rodríguez; Alberto Lamas 001; Jules Sanchez; Gianni Franchi; Ivan Donadello; Siham Tabik; David Filliat; Policarpo Cruz; Rosana Montes; Francisco Herrera (Inf. Fusion, 2022)

Greybox XAI: A Neural-Symbolic learning framework to produce interpretable predictions for image classification. - Adrien Bennetot; Gianni Franchi; Javier Del Ser; Raja Chatila 001; Natalia Díaz Rodríguez (Knowl. Based Syst., 2022)

Learning deep morphological networks with neural architecture search. - Yufei Hu; Nacim Belkhir; Jesús Angulo; Angela Yao; Gianni Franchi (Pattern Recognit., 2022)

The Robust Semantic Segmentation UNCV2023 Challenge Results. - Xuanlong Yu; Yi Zuo; Zitao Wang; Xiaowen Zhang; Jiaxuan Zhao; Yuting Yang 008; Licheng Jiao; Rui Peng; Xinyi Wang; Junpei Zhang; Kexin Zhang 003; Fang Liu 001; et al. (ICCV (Workshops), 2023)

Packed Ensembles for efficient uncertainty estimation. - Olivier Laurent 002; Adrien Lafage; Enzo Tartaglione; Geoffrey Daniel; Jean-Marc Martinez; Andrei Bursuc; Gianni Franchi (ICLR, 2023)

Improving CLIP Robustness with Knowledge Distillation and Self-Training. - Clement Laroudie; Andrei Bursuc; Mai Lan Ha; Gianni Franchi (CoRR, 2023)

How to effectively train an ensemble of Faster R-CNN object detectors to quantify uncertainty. - Denis Mbey Akola; Gianni Franchi (CoRR, 2023)

Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression. - Xuanlong Yu; Gianni Franchi; Jindong Gu; Emanuel Aldea (AAAI, 2024)

Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models. - Gianni Franchi; Olivier Laurent 002; Maxence Leguéry; Andrei Bursuc; Andrea Pilzer; Angela Yao (CVPR, 2024)

A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors. - Olivier Laurent 002; Emanuel Aldea; Gianni Franchi (ICLR, 2024)

NECO: NEural Collapse Based Out-of-distribution detection. - Mouïn Ben Ammar; Nacim Belkhir; Sebastian Popescu; Antoine Manzanera; Gianni Franchi (ICLR, 2024)

Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement. - Kai Xu; Rongyu Chen; Gianni Franchi; Angela Yao (ICLR, 2024)

Frustratingly Easy Test-Time Adaptation of Vision-Language Models. - Matteo Farina; Gianni Franchi; Giovanni Iacca; Massimiliano Mancini; Elisa Ricci 001 (NeurIPS, 2024)

InfraParis: A multi-modal and multi-task autonomous driving dataset. - Gianni Franchi; Marwane Hariat; Xuanlong Yu; Nacim Belkhir; Antoine Manzanera; David Filliat (WACV, 2024)

Learning to generate training datasets for robust semantic segmentation. - Marwane Hariat; Olivier Laurent 002; Rémi Kazmierczak; Shihao Zhang; Andrei Bursuc; Angela Yao; Gianni Franchi (WACV, 2024)

Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It. - Guoxuan Xia; Olivier Laurent 002; Gianni Franchi; Christos-Savvas Bouganis (CoRR, 2024)

Organizing Unstructured Image Collections using Natural Language. - Mingxuan Liu; Zhun Zhong; Jun Li; Gianni Franchi; Subhankar Roy; Elisa Ricci 001 (CoRR, 2024)

Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity. - Mouïn Ben Ammar; David Brellmann; Arturo Mendoza; Antoine Manzanera; Gianni Franchi (CoRR, 2024)

Benchmarking XAI Explanations with Human-Aligned Evaluations. - Rémi Kazmierczak; Steve Azzolin; Eloïse Berthier; Anna Hedström; Patricia Delhomme; Nicolas Bousquet 001; Goran Frehse; Massimiliano Mancini; Baptiste Caramiaux; Andrea Passerini; Gianni Franchi (CoRR, 2024)

Collaborative Instance Navigation: Leveraging Agent Self-Dialogue to Minimize User Input. - Francesco Taioli; Edoardo Zorzi; Gianni Franchi; Alberto Castellini; Alessandro Farinelli; Marco Cristani; Yiming Wang 002 (CoRR, 2024)

CLIP-QDA: An Explainable Concept Bottleneck Model. - Rémi Kazmierczak; Eloïse Berthier; Goran Frehse; Gianni Franchi (Trans. Mach. Learn. Res., 2024)

Encoding the Latent Posterior of Bayesian Neural Networks for Uncertainty Quantification. - Gianni Franchi; Andrei Bursuc; Emanuel Aldea; Séverine Dubuisson; Isabelle Bloch (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation. - Gianni Franchi; Nacim Belkhir; Dat Nguyen Trong; Guoxuan Xia; Andrea Pilzer (CVPR, 2025)

Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It. - Guoxuan Xia; Olivier Laurent 002; Gianni Franchi; Christos-Savvas Bouganis (ICLR, 2025)

Hierarchical Light Transformer Ensembles for Multimodal Trajectory Forecasting. - Adrien Lafage; Mathieu Barbier; Gianni Franchi; David Filliat (WACV, 2025)

Explainability and vision foundation models: A survey. - Rémi Kazmierczak; Eloïse Berthier; Goran Frehse; Gianni Franchi (Inf. Fusion, 2025)

Robust trajectory forecasting in autonomous systems using mixtures of Student's T-distributions with T-DistNet. - Adrien Lafage; Gianni Franchi; Mathieu Barbier; David Filliat (Pattern Recognit., 2025)

Explainability for Vision Foundation Models: A Survey. - Rémi Kazmierczak; Eloïse Berthier; Goran Frehse; Gianni Franchi (CoRR, 2025)

Concept-Based Mechanistic Interpretability Using Structured Knowledge Graphs. - Sofiia Chorna; Kateryna Tarelkina; Eloïse Berthier; Gianni Franchi (CoRR, 2025)

COOkeD: Ensemble-based OOD detection in the era of zero-shot CLIP. - Galadrielle Humblot-Renaux; Gianni Franchi; Sergio Escalera; Thomas B. Moeslund (CoRR, 2025)

Foundation models and Transformers for anomaly detection: A survey. - Mouïn Ben Ammar; Arturo Mendoza; Nacim Belkhir; Antoine Manzanera; Gianni Franchi (Inf. Fusion, 2026)