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Found 4 papers, 4 papers with code
PanopticNDT: Efficient and Robust Panoptic Mapping
As the application scenarios of mobile robots are getting more complex and challenging, scene understanding becomes increasingly crucial.
Ranked #2 on
Semantic Segmentation
on ScanNetV2
Efficient Multi-Task Scene Analysis with RGB-D Transformers
However, we show that the dual CNN-based encoder of EMSANet can be replaced with a single Transformer-based encoder.
Ranked #5 on
Semantic Segmentation
on ScanNetV2
Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments
In order to evaluate our multi-task approach, we extend the annotations of the common RGB-D indoor datasets NYUv2 and SUNRGB-D for instance segmentation and orientation estimation.
Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis
In this paper, we propose an efficient and robust RGB-D segmentation approach that can be optimized to a high degree using NVIDIA TensorRT and, thus, is well suited as a common initial processing step in a complex system for scene analysis on mobile robots.
