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Found 5 papers, 1 papers with code
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling
Training high-quality instance segmentation models requires an abundance of labeled images with instance masks and classifications, which is often expensive to procure.
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation
Our model builds a panoptic radiance field representation of any scene from just color images.
Learning 3D Semantic Segmentation with only 2D Image Supervision
With the recent growth of urban mapping and autonomous driving efforts, there has been an explosion of raw 3D data collected from terrestrial platforms with lidar scanners and color cameras.
Ranked #8 on
LIDAR Semantic Segmentation
on nuScenes
Dilated SpineNet for Semantic Segmentation
Scale-permuted networks have shown promising results on object bounding box detection and instance segmentation.
Ranked #5 on
Semantic Segmentation
on PASCAL VOC 2012 val
Virtual Multi-view Fusion for 3D Semantic Segmentation
Features from multiple per view predictions are finally fused on 3D mesh vertices to predict mesh semantic segmentation labels.
Ranked #12 on
Semantic Segmentation
on ScanNet
