38 citations · 42 across the 10 of their papers we have counts for
4 papers · 1 filter
3D-MOOD: Lifting 2D to 3D for Monocular Open-Set Object Detection
Yung-Hsu Yang, Luigi Piccinelli, Mattia Segu +6
Monocular 3D object detection is valuable for various applications such as robotics and AR/VR. Existing methods are confined to closed-set settings, where the training and testing…
One2Any: One-Reference 6D Pose Estimation for Any Object
Mengya Liu, Siyuan Li, Ajad Chhatkuli +3
6D object pose estimation remains challenging for many applications due to dependencies on complete 3D models, multi-view images, or training limited to specific object categories.…
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…
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…