Segmentation LiDAR
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| Reference | Sensors | Semantics | Sensing Modality Representations | Fusion Operation and Method | Fusion Level | Dataset(s) used |
|---|---|---|---|---|---|---|
| Chen et al., 2019 [pdf][ref] | LiDAR, visual camera | Road segmentation | RGB image, altitude difference image. Each processed by a CNN | Feature adaptation module, modified concatenation. | Middle | KITTI |
| Caltagirone et al., 2019 [pdf][ref] | LiDAR, vision camera | Road segmentation | LiDAR front-view depth images, RGB image. Each input processed by a FCN | Feature concatenation (For early and late fusion), weighted addition similar to gating network (for middle-level cross fusion) | Early, Middle, Late | KITTI |
| Erkent et al., 2018 [pdf][ref] | LiDAR, visual camera | Multiple 2D objects | LiDAR BEV occupancy grids (processed based on Bayesian filtering and tracking), RGB image (processed by a FCN with VGG16 backbone) | Feature concatenation | Middle | KITTI, self-recorded |
| Lv et al., 2018 [pdf][ref] | LiDAR, vision camera | Road segmentation | LiDAR BEV maps, RGB image. Each input processed by a FCN with dilated convolution operator. RGB image features are alo projected onto LiDAR BEV plane before fusion | Feature concatenation | Middle | KITTI |
| Wulff et al., 2018 [pdf][ref] | LiDAR, vision camera | Road segmentation. Alternatives: freespace, ego-lane detection | LiDAR BEV maps, RGB image projected onto BEV plane. Inputs processed by a FCN with UNet | Feature concatenation | Early | KITTI |
| Kim et al., 2018 [pdf][ref] | LiDAR, vision camera | 2D Off-road terrains | LiDAR voxel (processed by 3D convolution), RGB image (processed by ENet) | Addition | Early, Middle, Late | self-recorded |
| Yang et al., 2018 [pdf][ref] | LiDAR, vision camera | Road segmentation | LiDAR points (processed by PointNet++), RGB image (processed by FCN with VGG16 backbone) | Optimizing Conditional Random Field (CRF) | Late | KITTI |
| Gu et al., 2018 [pdf][ref] | LiDAR, visual camera | Road segmentation | LiDAR front-view depth and height maps (processed by a inverse-depth histogram based line scanning strategy), RGB image (processed by a FCN). | Optimizing Conditional Random Field | Late | KITTI |