Light-Weight RefineNet for Real-Time Semantic Segmentation

Understand

We consider an important task of effective and efficient semantic image segmentation.

• In particular, we adapt a powerful semantic segmentation architecture, called RefineNet, into the more compact one, suitable even for tasks requiring real-time performance on high-resolution inputs.
• To this end, we identify computationally expensive blocks in the original setup, and propose two modifications aimed to decrease the number of parameters and floating point operations.
• By doing that, we achieve more than twofold model reduction, while keeping the performance levels almost intact.