activity
20162025
most citedUniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

38 citations · 104 across the 12 of their papers we have counts for

collaborators

14 papers

cs.CV2025

Video Depth Propagation

Luigi Piccinelli, Thiemo Wandel, Christos Sakaridis +2

Depth estimation in videos is essential for visual perception in real-world applications. However, existing methods either rely on simple frame-by-frame monocular models, leading t…

cs.CV2025

DGFusion: Depth-Guided Sensor Fusion for Robust Semantic Perception

Tim Broedermannn, Christos Sakaridis, Luigi Piccinelli +2

Robust semantic perception for autonomous vehicles relies on effectively combining multiple sensors with complementary strengths and weaknesses. State-of-the-art sensor fusion appr…

cs.CV2025

UniK3D: Universal Camera Monocular 3D Estimation

Luigi Piccinelli, Christos Sakaridis, Mattia Segu +4

Monocular 3D estimation is crucial for visual perception. However, current methods fall short by relying on oversimplified assumptions, such as pinhole camera models or rectified i…

cs.CV2025★ 38 cited

UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

Luigi Piccinelli, Christos Sakaridis, Yung-Hsu Yang +4

Accurate monocular metric depth estimation (MMDE) is crucial to solving downstream tasks in 3D perception and modeling. However, the remarkable accuracy of recent MMDE methods is c…

cs.CV2021

MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation

Jonas Heylen, Mark De Wolf, Bruno Dawagne +5

Monocular 3D object detection has recently shown promising results, however there remain challenging problems. One of those is the lack of invariance to different camera intrinsic…

cs.CV2021★ 1 cited

ACDC: The Adverse Conditions Dataset with Correspondences for Robust Semantic Driving Scene Perception

Christos Sakaridis, Haoran Wang, Ke Li +6

Level-5 driving automation requires a robust visual perception system that can parse input images under any condition. However, existing driving datasets for dense semantic percept…