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

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))
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support