---
language: en
tags:
  - point-cloud
  - 3d-classification
  - pytorch
  - pointnet
  - modelnet10
license: mit
---

# Vanilla PointNet — ModelNet10 Classifier

Simplified PointNet (no T-Nets) for 3D object classification on ModelNet10.

## Architecture
| Stage | Layers |
|-------|--------|
| Feature Extraction | Conv1d(3→64→128→1024) + BN + ReLU |
| Global Aggregation | Global max-pool → 1024-d vector |
| Classification     | FC(1024→512→256→10) + BN + Dropout |

## Classes
`bathtub · bed · chair · desk · dresser · monitor · night_stand · sofa · table · toilet`

## Usage
```python
import torch
from model import VanillaPointNet

model = VanillaPointNet(num_classes=10)
model.load_state_dict(torch.load("pytorch_model.bin", map_location="cpu"))
model.eval()

pts = torch.randn(1, 3, 1024)   # (B, 3, N)
print(model(pts).argmax(1))
```