Joint recovery algorithms using difference of innovations for distributed compressed sensing. - Diego Valsesia; Giulio Coluccia; Enrico Magli (ACSSC, 2013)

Graded quantization: Democracy for multiple descriptions in compressed sensing. - Diego Valsesia; Giulio Coluccia; Enrico Magli (ICASSP, 2013)

Smoothness-constrained image recovery from block-based random projections. - Giulio Coluccia; Diego Valsesia; Enrico Magli (MMSP, 2013)

Spatially scalable compressed image sensing with hybrid transform and inter-layer prediction model. - Diego Valsesia; Enrico Magli (MMSP, 2013)

Compressive signal processing with circulant sensing matrices. - Diego Valsesia; Enrico Magli (ICASSP, 2014)

A hardware-friendly architecture for onboard rate-controlled predictive coding of hyperspectral and multispectral images. - Diego Valsesia; Enrico Magli (ICIP, 2014)

A Novel Rate Control Algorithm for Onboard Predictive Coding of Multispectral and Hyperspectral Images. - Diego Valsesia; Enrico Magli (IEEE Trans. Geosci. Remote. Sens., 2014)

Scale-robust compressive camera fingerprint matching with random projections. - Diego Valsesia; Giulio Coluccia; Tiziano Bianchi; Enrico Magli (ICASSP, 2015)

Image retrieval based on compressed camera sensor fingerprints. - Diego Valsesia; Giulio Coluccia; Tiziano Bianchi; Enrico Magli (ICME, 2015)

Graded Quantization for Multiple Description Coding of Compressive Measurements. - Diego Valsesia; Giulio Coluccia; Enrico Magli (IEEE Trans. Commun., 2015)

Large-Scale Image Retrieval Based on Compressed Camera Identification. - Diego Valsesia; Giulio Coluccia; Tiziano Bianchi; Enrico Magli (IEEE Trans. Multim., 2015)

Universal encoding of multispectral images. - Diego Valsesia; Petros T. Boufounos (ICASSP, 2016)

Toothpic: Who took this picture? - Diego Valsesia; Giulio Coluccia; Tiziano Bianchi; Enrico Magli (ICME Workshops, 2016)

SparseHash: Embedding Jaccard coefficient between supports of signals. - Diego Valsesia; Sophie M. Fosson; Chiara Ravazzi; Tiziano Bianchi; Enrico Magli (ICME Workshops, 2016)

Multispectral image compression using universal vector quantization. - Diego Valsesia; Petros T. Boufounos (ITW, 2016)

Imaging using random projections: compression, communication, camera identification. - Diego Valsesia (2016)

Fast and Lightweight Rate Control for Onboard Predictive Coding of Hyperspectral Images. - Diego Valsesia; Enrico Magli (IEEE Geosci. Remote. Sens. Lett., 2017)

Binary Adaptive Embeddings From Order Statistics of Random Projections. - Diego Valsesia; Enrico Magli (IEEE Signal Process. Lett., 2017)

User Authentication via PRNU-Based Physical Unclonable Functions. - Diego Valsesia; Giulio Coluccia; Tiziano Bianchi; Enrico Magli (IEEE Trans. Inf. Forensics Secur., 2017)

Image Denoising with Graph-Convolutional Neural Networks. - Diego Valsesia; Giulia Fracastoro; Enrico Magli (ICIP, 2019)

Learning Localized Generative Models for 3D Point Clouds via Graph Convolution. - Diego Valsesia; Giulia Fracastoro; Enrico Magli (ICLR (Poster), 2019)

Deep Learning For Super-Resolution Of Unregistered Multi-Temporal Satellite Images. - Andrea Bordone Molini; Diego Valsesia; Giulia Fracastoro; Enrico Magli (WHISPERS, 2019)

ToothPic: Camera-Based Image Retrieval on Large Scales. - Diego Valsesia; Giulio Coluccia; Tiziano Bianchi; Enrico Magli (IEEE Multim., 2019)

Analysis of SparseHash: An efficient embedding of set-similarity via sparse projections. - Diego Valsesia; Sophie M. Fosson; Chiara Ravazzi; Tiziano Bianchi; Enrico Magli (Pattern Recognit. Lett., 2019)

High-Throughput Onboard Hyperspectral Image Compression With Ground-Based CNN Reconstruction. - Diego Valsesia; Enrico Magli (IEEE Trans. Geosci. Remote. Sens., 2019)

Sampling of Graph Signals via Randomized Local Aggregations. - Diego Valsesia; Giulia Fracastoro; Enrico Magli (IEEE Trans. Signal Inf. Process. over Networks, 2019)

Learning Graph-Convolutional Representations for Point Cloud Denoising. - Francesca Pistilli; Giulia Fracastoro; Diego Valsesia; Enrico Magli (ECCV (20), 2020)

Point Cloud Normal Estimation with Graph-Convolutional Neural Networks. - Francesca Pistilli; Giulia Fracastoro; Diego Valsesia; Enrico Magli (ICME Workshops, 2020)

Deepsum++: Non-Local Deep Neural Network for Super-Resolution of Unregistered Multitemporal Images. - Andrea Bordone Molini; Diego Valsesia; Giulia Fracastoro; Enrico Magli (IGARSS, 2020)

Towards Deep Unsupervised Sar Despeckling with Blind-Spot Convolutional Neural Networks. - Andrea Bordone Molini; Diego Valsesia; Giulia Fracastoro; Enrico Magli (IGARSS, 2020)

Detection of Solar Coronal Mass Ejections from Raw Images with Deep Convolutional Neural Networks. - Diego Valsesia; Andrea Grippi; Enrico Magli; Roberto Susino; Daniele Telloni; Gianalfredo Nicolini; Marta Casti; Angelo Fabio Mulone; Rosario Messineo (IGARSS, 2020)

NIR image colorization with graph-convolutional neural networks. - Diego Valsesia; Giulia Fracastoro; Enrico Magli (VCIP, 2020)

Deep learning methods for SAR image despeckling: trends and perspectives. - Giulia Fracastoro; Enrico Magli; Giovanni Poggi; Giuseppe Scarpa; Diego Valsesia; Luisa Verdoliva (CoRR, 2020)

DeepSUM: Deep Neural Network for Super-Resolution of Unregistered Multitemporal Images. - Andrea Bordone Molini; Diego Valsesia; Giulia Fracastoro; Enrico Magli (IEEE Trans. Geosci. Remote. Sens., 2020)

Deep Graph-Convolutional Image Denoising. - Diego Valsesia; Giulia Fracastoro; Enrico Magli (IEEE Trans. Image Process., 2020)

Denoise and Contrast for Category Agnostic Shape Completion. - Antonio Alliegro; Diego Valsesia; Giulia Fracastoro; Enrico Magli; Tatiana Tommasi (CVPR, 2021)

Deep Multiframe Enhancement for Motion Prediction in Video Compression. - Nicola Prette; Diego Valsesia; Tiziano Bianchi (ICECS, 2021)

Spatial Light Modulator-Based Architecture to Implement a Super-Resolved Compressive Instrument for Earth Observation. - Valentina Raimondi; Luigi Acampora; Gabriele Amato; Massimo Baldi; Dirk Berndt; Alberto Bianchi; Tiziano Bianchi; Donato Borrelli; Valentina Colcelli; Chiara Corti; Francesco Corti; Marco Corti; et al. (IGARSS, 2021)

Self-supervised learning for joint SAR and multispectral land cover classification. - Antonio Montanaro; Diego Valsesia; Giulia Fracastoro; Enrico Magli (CoRR, 2021)

Learning Robust Graph-Convolutional Representations for Point Cloud Denoising. - Francesca Pistilli; Giulia Fracastoro; Diego Valsesia; Enrico Magli (IEEE J. Sel. Top. Signal Process., 2021)

Learning Localized Representations of Point Clouds With Graph-Convolutional Generative Adversarial Networks. - Diego Valsesia; Giulia Fracastoro; Enrico Magli (IEEE Trans. Multim., 2021)

Signal Compression via Neural Implicit Representations. - Francesca Pistilli; Diego Valsesia; Giulia Fracastoro; Enrico Magli (ICASSP, 2022)

Exploring the Solution Space of Linear Inverse Problems with GAN Latent Geometry. - Antonio Montanaro; Diego Valsesia; Enrico Magli (ICIP, 2022)

Super-Resolved Multi-Temporal Segmentation with Deep Permutation-Invariant Networks. - Diego Valsesia; Enrico Magli (IGARSS, 2022)

Cross-modal Learning for Image-Guided Point Cloud Shape Completion. - Emanuele Aiello; Diego Valsesia; Enrico Magli (NeurIPS, 2022)

Rethinking the compositionality of point clouds through regularization in the hyperbolic space. - Antonio Montanaro; Diego Valsesia; Enrico Magli (NeurIPS, 2022)

Semi-Supervised Learning for Joint SAR and Multispectral Land Cover Classification. - Antonio Montanaro; Diego Valsesia; Giulia Fracastoro; Enrico Magli (IEEE Geosci. Remote. Sens. Lett., 2022)

Speckle2Void: Deep Self-Supervised SAR Despeckling With Blind-Spot Convolutional Neural Networks. - Andrea Bordone Molini; Diego Valsesia; Giulia Fracastoro; Enrico Magli (IEEE Trans. Geosci. Remote. Sens., 2022)

Permutation Invariance and Uncertainty in Multitemporal Image Super-Resolution. - Diego Valsesia; Enrico Magli (IEEE Trans. Geosci. Remote. Sens., 2022)

Multi-Level Fusion for Burst Super-Resolution with Deep Permutation-Invariant Conditioning. - Martina Cilia; Diego Valsesia; Giulia Fracastoro; Enrico Magli (ICASSP, 2023)

Towards Hyperbolic Regularizers For Point Cloud Part Segmentation. - Antonio Montanaro; Diego Valsesia; Enrico Magli (ICASSP, 2023)

Onboard Processing Capabilities of an Earth Observation Compressive Sensing Payload. - Tiziano Bianchi; Martina Cilia; Enrico Magli; Andrea Migliorati; Nicola Prette; Diego Valsesia (IGARSS, 2023)

Diffraction Efficiency-Aware Reconstruction for Compressive Sensing in the Mid-Infrared. - Tiziano Bianchi; Donatella Guzzi; Cinzia Lastri; Enrico Magli; Vanni Nardino; Lorenzo Palombi; Nicola Prette; Valentina Raimondi; Diego Valsesia (IGARSS, 2023)

Proba-V Multi-Temporal Super-Resolution Guided by Sentinel-2. - Gabriele Inzerillo; Diego Valsesia; Enrico Magli; Fabrizio Niro; Erminia De Grandis (IGARSS, 2023)

Towards Unsupervised Multi-Temporal Satellite Image Super-Resolution. - Nicola Prette; Diego Valsesia; Tiziano Bianchi; Enrico Magli (IGARSS, 2023)

On the Use of Machine Learning Algorithms to Improve GNSS Products. - Andrea Nardin; Fabio Dovis; Diego Valsesia; Enrico Magli; Chiara Leuzzi; Rosario Messineo; Hugo Sobreira; Richard Swinden (PLANS, 2023)

RAN-GNNs: Breaking the Capacity Limits of Graph Neural Networks. - Diego Valsesia; Giulia Fracastoro; Enrico Magli (IEEE Trans. Neural Networks Learn. Syst., 2023)

Degradation-Aware Self-Supervised Multi-Temporal Super-Resolution. - Matteo Impieri; Diego Valsesia; Tiziano Bianchi; Enrico Magli (IGARSS, 2024)

Hybrid Recurrent-Attentive Neural Network for Onboard Predictive Hyperspectral Image Compression. - Diego Valsesia; Tiziano Bianchi; Enrico Magli (IGARSS, 2024)

MotionCraft: Physics-Based Zero-Shot Video Generation. - Antonio Montanaro; Luca Savant Aira; Emanuele Aiello; Diego Valsesia; Enrico Magli (NeurIPS, 2024)

Synthetic Data Pretraining for Hyperspectral Image Super-Resolution. - Emanuele Aiello; Mirko Agarla; Diego Valsesia; Paolo Napoletano; Tiziano Bianchi; Enrico Magli; Raimondo Schettini (IEEE Access, 2024)

Fast Inference in Denoising Diffusion Models via MMD Finetuning. - Emanuele Aiello; Diego Valsesia; Enrico Magli (IEEE Access, 2024)

Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow. - Luca Savant Aira; Diego Valsesia; Andrea Bordone Molini; Giulia Fracastoro; Enrico Magli; Andrea Mirabile (IEEE Access, 2024)

Deep Lidar-guided Image Deblurring. - Ziyao Yi; Diego Valsesia; Tiziano Bianchi; Enrico Magli (CoRR, 2024)

Onboard Deep Lossless and Near-Lossless Predictive Coding of Hyperspectral Images With Line-Based Attention. - Diego Valsesia; Tiziano Bianchi; Enrico Magli (IEEE Trans. Geosci. Remote. Sens., 2024)

DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching. - Emanuele Aiello; Umberto Michieli; Diego Valsesia; Mete Ozay; Enrico Magli (CVPR, 2025)

Efficient Onboard Multitask AI Architecture Based on Self-Supervised Learning. - Gabriele Inzerillo; Diego Valsesia; Enrico Magli (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

Modeling Uncertainty for Gaussian Splatting. - Luca Savant Aira; Diego Valsesia; Enrico Magli (IEEE Trans. Neural Networks Learn. Syst., 2025)

Compress-Align-Detect: onboard change detection from unregistered images. - Gabriele Inzerillo; Diego Valsesia; Aniello Fiengo; Enrico Magli (CoRR, 2025)

Onboard Hyperspectral Super-Resolution with Deep Pushbroom Neural Network. - Davide Piccinini; Diego Valsesia; Enrico Magli (CoRR, 2025)