A General Notations
–Neural Information Processing Systems
In Tab. 1, we provide a comprehensive summary of the general notations used throughout the paper Definition B.1 (Quasi-isometric Properties), Let Definition B.2 (Local Quasi-isometric Properties), Local quasi-isometry refers to a function whereby The proposed quasi-isometric loss benefits from the incorporation of a local distance-preserving condition. In Tab. 2, we report We elaborate on the specifics of the experimental setup in Tab. 3. We impose our quasi-isometric loss and object-wise depth map loss using the output feature extracted from DLAUp. This extracted object descriptor is subsequently utilized to compute the loss. We provide additional qualitative results using the MonoCon and "MonoCon + Ours" as discussed Tab. Geometry uncertainty projection network for monocular 3d object detection.
Neural Information Processing Systems
Nov-20-2025, 01:58:24 GMT
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- Information Technology > Artificial Intelligence
- Machine Learning (0.72)
- Vision (0.50)
- Information Technology > Artificial Intelligence