3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Matching Anything by Segmenting Anything
Siyuan Li, Lei Ke, Martin Danelljan +4
The robust association of the same objects across video frames in complex scenes is crucial for many applications, especially Multiple Object Tracking (MOT). Current methods predom…
cs.CV2024
Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning
Rui Li, Tobias Fischer, Mattia Segu +3
Recovering the 3D scene geometry from a single view is a fundamental yet ill-posed problem in computer vision. While classical depth estimation methods infer only a 2.5D scene repr…
cs.CV2024★ 3 cited
UniDepth: Universal Monocular Metric Depth Estimation
Luigi Piccinelli, Yung-Hsu Yang, Christos Sakaridis +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…