FenceMask: A Data Augmentation Approach for Pre-extracted Image Features

Understand

We propose a novel data augmentation method named 'FenceMask' that exhibits outstanding performance in various computer vision tasks.

• It is based on the 'simulation of object occlusion' strategy, which aim to achieve the balance between object occlusion and information retention of the input data.
• By enhancing the sparsity and regularity of the occlusion block, our augmentation method overcome the difficulty of small object augmentation and notably improve performance over baselines.
• Sufficient experiments prove the performance of our method is better than other simulate object occlusion approaches.