AMUSE: Adaptive Multi-Segment Encoding for Dataset Watermarking

Understand

Curating high quality datasets that play a key role in the emergence of new AI applications requires considerable time, money, and computational resources.

• So, effective ownership protection of datasets is becoming critical.
• Recently, to protect the ownership of an image dataset, imperceptible watermarking techniques are used to store ownership information (i.e., watermark) into the individual image samples.
• Embedding the entire watermark into all samples leads to significant redundancy in the embedded information which damages the watermarked dataset quality and extraction accuracy.