coordinate attention

**Coordinate Attention** is a **lightweight attention mechanism that encodes channel relationships and long-range spatial dependencies** — by decomposing global pooling into two 1D operations (horizontal and vertical), preserving positional information that SE-Net's global average pooling discards. **How Does Coordinate Attention Work?** - **Horizontal Pool**: Average pool along the width dimension -> $z_h(h) in mathbb{R}^{C imes H imes 1}$. - **Vertical Pool**: Average pool along the height dimension -> $z_w(w) in mathbb{R}^{C imes 1 imes W}$. - **Transform**: Concatenate, pass through shared 1×1 conv + BN + activation, then split. - **Attention**: Sigmoid-activated 1×1 conv produces 2D spatial-aware channel attention maps. - **Paper**: Hou et al. (2021). **Why It Matters** - **Position-Aware**: Unlike SE (global avg pool -> loses position), Coordinate Attention preserves spatial structure. - **Lightweight**: Minimal additional parameters and FLOPs. - **Object Detection**: Particularly effective for dense prediction tasks where spatial position matters. **Coordinate Attention** is **SE with spatial awareness** — encoding directional position information into channel attention for better localization.