Shared Visual Structure Makes Extra Source Data Helpful

Source-Specific Features Can Consume Model Capacity

When is it reasonable to mix a large set of public web photos into a product-image training set?

A very large network trained long enough can, in principle, learn from two different image collections without an unavoidable tradeoff.

Complete the capacity requirement before adding more training data

Match each training-scenario element with its role in the learning argument.

Order the reasoning steps for deciding whether to add public web photos to training.

Why a larger model can learn from two image sources

Whether to Use 180,000 Public-Web Photos Alongside 4,000 App Photos

When is it reasonable to mix outside web images with app-captured images?

What does the 40:1 dataset ratio suggest in this example?

Combining a second image source always improves model performance.