Densely Nested Top-Down Flows for Salient Object Detection

Understand

With the goal of identifying pixel-wise salient object regions from each input image, salient object detection (SOD) has been receiving great attention in recent years.

• One kind of mainstream SOD methods is formed by a bottom-up feature encoding procedure and a top-down information decoding procedure.
• While numerous approaches have explored the bottom-up feature extraction for this task, the design on top-down flows still remains under-studied.
• To this end, this paper revisits the role of top-down modeling in salient object detection and designs a novel densely nested top-down flows (DNTDF)-based framework.