datasets. Position-specific attention cells (‘Pos-Specific’) consistently outperform position-agnostic attention cells (‘Pos-Agnostic’).[]{data-label="table-differentiable"}

  ----- ------------------------------- -- -- ----------- ----------- --------------- -- -- ----------- ----------- --------------- --
                                                                                                                                    
        Model                                    Top-1       Top-5     $\Delta$Top-1           Top-1       Top-5     $\Delta$Top-1  
  I3D   Backbone [@carreira2017quo]              75.58       92.93           -                 27.38       54.29           -        
        Non-local [@wang2018non]                 76.87       93.44         1.29                28.54       55.35         1.16       
        Ours - Pos-Agnostic                      77.56       93.63         1.98                28.18       55.01         0.80       
        Ours - Pos-Specific                    **77.86**   **93.75**     **2.28**            **29.58**   **56.62**     **2.20**     
  S3D   Backbone [@xie2018rethinking]            76.15       93.22           -                 27.69       54.68           -        
        Non-local [@wang2018non]                 77.56       93.68         1.41                29.52       56.91         1.83       
        Ours - Pos-Agnostic                      77.82       93.72         1.67                29.19       55.96         1.50       
        Ours - Pos-Specific                    **78.51**   **93.88**     **2.36**            **29.82**   **57.02**     **2.13**     
  ----- ------------------------------- -- -- ----------- ----------- --------------- -- -- ----------- ----------- --------------- --

  : Search results on Kinetics-600 and MiT using the differentiable method. Our attention cells consistently outperform non-local blocks on all the combinations of backbones and datasets. Position-specific attention cells (‘Pos-Specific’) consistently outperform position-agnostic attention cells (‘Pos-Agnostic’).[]{data-label="table-differentiable"}

  ----- ------------------------------- -- -- ----------- ----------- --------------- -- -- ----------- ----------- --------------- --
                                                                                                                                    
        Model                                    Top-1       Top-5     $\Delta$Top-1           Top-1       Top-5     $\Delta$Top-1  
  I3D   Backbone [@carreira2017quo]              61.14       82.77           -                 20.01       42.42           -        
        Non-local [@wang2018non]                 64.88       85.77         3.74                21.86     **46.59**       1.85       
        Ours - GPB                               65.81       87.04         4.67                21.83       45.45         1.82       
        Ours - Differentiable                  **66.81**   