Concatenation Affinity is a type of affinity or self-similarity function between two points $\mathbb{x_{i}}$ and $\mathbb{x_{j}}$ that uses a concatenation function:
$$ f\left(\mathbb{x_{i}}, \mathbb{x_{j}}\right) = \text{ReLU}\left(\mathbb{w}^{T}_{f}\left[\theta\left(\mathbb{x}_{i}\right), \phi\left(\mathbb{x}_{j}\right)\right]\right)$$
Here $\left[·, ·\right]$ denotes concatenation and $\mathbb{w}_{f}$ is a weight vector that projects the concatenated vector to a scalar.
Source: Non-local Neural NetworksPaper | Code | Results | Date | Stars |
---|
Task | Papers | Share |
---|---|---|
Action Classification | 1 | 14.29% |
Action Recognition | 1 | 14.29% |
Instance Segmentation | 1 | 14.29% |
Keypoint Detection | 1 | 14.29% |
Object Detection | 1 | 14.29% |
Pose Estimation | 1 | 14.29% |
Video Classification | 1 | 14.29% |