15 papers
Robust Promptable Video Object Segmentation
Sohyun Lee, Yeho Gwon, Lukas Hoyer +3
The performance of promptable video object segmentation (PVOS) models substantially degrades under input corruptions, which prevents PVOS deployment in safety-critical domains. Thi…
Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark
Yiting Wang, Nolwenn Peyratout, Tim Brodermann +13
This paper presents the report of the URVIS 2026 challenge on adverse-to-extreme panoptic segmentation. As the first challenge of its kind, it attracted 17 registered participants…
AURORA-KITTI: Any-Weather Depth Completion and Denoising in the Wild
Yiting Wang, Tim Brödermann, Hamed Haghighi +4
Robust depth completion is fundamental to real-world 3D scene understanding, yet existing RGB-LiDAR fusion methods degrade significantly under adverse weather, where both camera im…
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…
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…
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…