Frustum VoxNet (YOLO v3+3D ResNetFCN6)

Reported on 6 benchmarks across 6 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology4 results

3DonSUN-RGBD val
Inference Speed (s)· 2019-10-12
0.048
SOTA
Frustum VoxNet for 3D object detection from RGB-D or Depth images arXiv:1910.05483
2D ClassificationonSUN-RGBD val
Inference Speed (s)· 2019-10-12
0.048
SOTA
Frustum VoxNet for 3D object detection from RGB-D or Depth images arXiv:1910.05483
2D Object DetectiononSUN-RGBD val
Inference Speed (s)· 2019-10-12
0.048
SOTA
Frustum VoxNet for 3D object detection from RGB-D or Depth images arXiv:1910.05483
16konSUN-RGBD val
Inference Speed (s)· 2019-10-12
0.048
SOTA
Frustum VoxNet for 3D object detection from RGB-D or Depth images arXiv:1910.05483

Computer Vision2 results

Object DetectiononSUN-RGBD val
Inference Speed (s)· 2019-10-12
0.048
SOTA
Frustum VoxNet for 3D object detection from RGB-D or Depth images arXiv:1910.05483
3D Object DetectiononSUN-RGBD val
Inference Speed (s)· 2019-10-12
0.048
SOTA
Frustum VoxNet for 3D object detection from RGB-D or Depth images arXiv:1910.05483