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Stefano Mattoccia

Full Professor

University of Bologna

Italy

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About

Stefano Mattoccia is an Associate Professor at the University of Bologna, Italy. His research areas include depth estimation, active stereo vision, and self-supervised learning techniques, as evidenced by his recent publications. Notable works include explorations of monocular depth perception and applications for low-power processing in real-time scenarios.

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Collaborators (2)

ELENA TOTH

Full Professor

University of Bologna

ITALY

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Luigi Di Stefano

University of Bologna

ITALY

View details

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Stefano Mattoccia

Research Interests

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About

Articles (33)

Towards Event‐Based Stereo Depth Estimation at Millisecond Resolution

Zero-Shot Neural Architecture Search for Efficient Deep Stereo Matching

DINO-SLAM: DINO-Informed RGB-D SLAM for Neural Implicit and Explicit Representations

FGDepth: Fine-Grained Boundary Perception Enhancement in Self-Supervised Indoor Depth Estimation

How NeRFs and 3-D Gaussian Splatting Are Reshaping SLAM: A Survey

MAGiSt3R: Multi-agent Feed-Forward 3D Reconstruction from Monocular RGB Videos

ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device

Active Stereo in the Wild through Virtual Pattern Projection

CabNIR: A Benchmark for In-Vehicle Infrared Monocular Depth Estimation

Depth AnyEvent: A Cross-Modal Distillation Paradigm for Event-Based Monocular Depth Estimation

Drive with the Flow

HS-SLAM: Hybrid Representation with Structural Supervision for Improved Dense SLAM

Learnable Fractional Reaction-Diffusion Dynamics for Under-Display ToF Imaging and Beyond

NTIRE 2025 Challenge on HR Depth From Images of Specular and Transparent Surfaces

Self-supervised Monocular Depth Estimation for Dynamic Objects with Ground Propagation

Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail

ToF-Splatting: Dense SLAM using Sparse Time-of-Flight Depth and Multi-Frame Integration

Depth on Demand: Streaming Dense Depth from a Low Frame Rate Active Sensor

LiDAR-Event Stereo Fusion with Hallucinations

Booster: A Benchmark for Depth From Images of Specular and Transparent Surfaces

Neural Disparity Refinement

Self-supervised depth super-resolution with contrastive multiview pre-training

Real-Time Self-Supervised Monocular Depth Estimation Without GPU

Energy-Quality Scalable Monocular Depth Estimation on Low-Power CPUs

Monitoring Social Distancing With Single Image Depth Estimation

Monocular Depth Perception on Microcontrollers for Edge Applications

Depth Restoration in Under-Display Time-of-Flight Imaging

Continual Adaptation for Deep Stereo

On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge

Beyond the Baseline: 3D Reconstruction of Tiny Objects With Single Camera Stereo Robot

Real-Time Single Image Depth Perception in the Wild with Handheld Devices

Good Cues to Learn From Scratch a Confidence Measure for Passive Depth Sensors

Unsupervised Domain Adaptation for Depth Prediction from Images

Collaborators (2)

ELENA TOTH

Luigi Di Stefano

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