Model Zoo (Pretrained Models)
We provide the training logs & pretrained models in column our released trained with the improved training strategies proposed by our PointNeXt through Google Drive.
TP: Throughput (instance per second) measured using an NVIDIA Tesla V100 32GB GPU and a 32 core Intel Xeon @ 2.80GHz CPU.
ScanObjectNN (Hardest variant) Classification
Throughput is measured with 128 x 1024 points.
| name | OA/mAcc (Original) | OA/mAcc (our released) | #params | FLOPs | Throughput (ins./sec.) |
|---|---|---|---|---|---|
| PointNet | 68.2 / 63.4 | 75.2 / 71.4 | 3.5M | 1.0G | 4212 |
| DGCNN | 78.1 / 73.6 | 86.1 / 84.3 | 1.8M | 4.8G | 402 |
| PointMLP | 85.4±1.3 / 83.9±1.5 | 87.7 / 86.4 | 13.2M | 31.4G | 191 |
| PointNet++ | 77.9 / 75.4 | 86.2 / 84.4 | 1.5M | 1.7G | 1872 |
| PointNeXt-S | 87.7±0.4 / 85.8±0.6 | 88.20 / 86.84 | 1.4M | 1.64G | 2040 |
| Pix4Point | 87.9 / 86.7 | 87.9 / 86.7 | 22.6M | 28.0G | - |
| PointVector | 87.8±0.4 / 86.2±0.5 | 88.17 / 86.69 | 1.55 | - | 901 |
S3IDS (6-fold) Segmentation
Throughput (TP) is measured with 16 x 15000 points.
| name | mIoU/OA/mAcc (Original) | mIoU/OA/mAcc (our released) | #params | FLOPs | TP |
|---|---|---|---|---|---|
| PointNet++ | 54.5 / 81.0 / 67.1 | 68.1 / 87.6 / 78.4 | 1.0M | 7.2G | 186 |
| PointNeXt-S | 68.0 / 87.4 / 77.3 | 68.0 / 87.4 / 77.3 | 0.8M | 3.6G | 227 |
| PointNeXt-B | 71.5 / 88.8 / 80.2 | 71.5 / 88.8 / 80.2 | 3.8M | 8.8G | 158 |
| PointNeXt-L | 73.9 / 89.8 / 82.2 | 73.9 / 89.8 / 82.2 | 7.1M | 15.2G | 115 |
| PointNeXt-XL | 74.9 / 90.3 / 83.0 | 74.9 / 90.3 / 83.0 | 41.6M | 84.8G | 46 |
| PointVector-L | 77.4 / 91.4 / 85.5 | 77.4 / 91.4 / 85.5 | 4.2M | 10.7G | 98 |
| PointVector-XL | 78.4 / 91.9 / 86.1 | 78.4 / 91.9 / 86.1 | 24.1M | 58.5G | 40 |
S3DIS (Area 5) Segmentation
Throughput (TP) is measured with 16 x 15000 points.
| name | mIoU/OA/mAcc (Original) | mIoU/OA/mAcc (our released) | #params | FLOPs | TP |
|---|---|---|---|---|---|
| PointNet++ | 53.5 / 83.0 / - | 63.6 / 88.3 / 70.2 | 1.0M | 7.2G | 186 |
| ASSANet | 63.0 / - /- | 65.8 / 88.9 / 72.2 | 2.4M | 2.5G | 228 |
| ASSANet-L | 66.8 / - / - | 68.0 / 89.7/ 74.3 | 115.6M | 36.2G | 81 |
| PointNeXt-S | 63.4±0.8 / 87.9±0.3 / 70.0±0.7 | 64.2 / 88.2 / 70.7 | 0.8M | 3.6G | 227 |
| PointNeXt-B | 67.3±0.2 / 89.4±0.1 / 73.7±0.6 | 67.5 / 89.4 / 73.9 | 3.8M | 8.8G | 158 |
| PointNeXt-L | 69.0±0.5 / 90.0±0.1 / 75.3±0.8 | 69.3 / 90.1 / 75.7 | 7.1M | 15.2G | 115 |
| PointNeXt-XL | 70.5±0.3 / 90.6±0.2 / 76.8±0.7 | 71.1 / 91.0 / 77.2 | 41.6M | 84.8G | 46 |
| Pix4Point | 69.6 / 89.9 / 75.2 | 69.6 / 89.9 / 75.2 | 23.7M | 190G | - |
| PointVector-L | 71.2 / 90.8 / 77.3 | 71.2 / 90.8 / 77.3 | - | - | - |
| PointVector-XL | 72.3 / 91.0 / 78.1 | 72.61 / 91.59 / 78.3 | 24.1M | 58.5G | 40 |
ShapeNetpart Part Segmentation
Throughput (TP) is measured with 64*2048 points.
| name | Ins. mIoU / Cat. mIoU (Original) | Ins. mIoU / Cat. mIoU (our released) |
|---|---|---|
| PointNet++ | 85.1/81.9 | |
| PointNeXt-S | 86.7±0.0 / 84.4±0.2 | 86.7 / 84.2 |
| PointNeXt-S (C=64) | 86.9±0.0 / 84.8±0.5 | 86.9 / 85.2 |
| PointNeXt-S (C=160) | 87.0±0.1 / 85.2±0.1 | 87.1 / 85.4 |
| Pix4Point | 86.8 / 85.6 | 86.8 / 85.6 |
| PointVector-S (C=64) | 86.9 / - | 86.9 / 85.05 |
ModelNet40 Classificaiton
| name | OA/mAcc (Original) | OA/mAcc (our released) | #params | FLOPs | Throughput (ins./sec.) |
|---|---|---|---|---|---|
| PointNet++ | 91.9 / - | 93.0 / 90.7 | 1.5M | 1.7G | 1872 |
| PointNeXt-S (C=64) | 93.7±0.3 / 90.9±0.5 | 94.0 / 91.1 | 4.5M | 6.5G | 2033 |
| PointVector-S (C=64) | 93.5±0.2 / 91.0±0.5 | 93.68 / 91.53 | - | - | - |