Search Results for author:
Found 2 papers, 0 papers with code
SparseFormer: Attention-based Depth Completion Network
This remains a challenging problem due to the low density, non-uniform and outlier-prone 3D landmarks produced by SfM and SLAM pipelines.
Disentangling Monocular 3D Object Detection
In this paper we propose an approach for monocular 3D object detection from a single RGB image, which leverages a novel disentangling transformation for 2D and 3D detection losses and a novel, self-supervised confidence score for 3D bounding boxes.
3D Object Detection From Monocular Images
Disentanglement
+3
