title: Negative Padding in Convolution (Caffe)
body: <p>I have a vector which consists of a concatenation the features of a video sequence across 7 frames.<br>
  I would like to apply 1D convolution to this vector such that only a part of a frame is processed.<br>
  Say a feature vector for one frame has the length 10 </p>
  
  <ul>
  <li>my input feature vector would be of total length 7 x 10 = 70 </li>
  </ul>
  
  <p>Now I want two convolutions to work on different parts of that vector</p>
  
  <ul>
  <li>conv1 should treat the features 1:5   </li>
  <li>conv2 should treat 6:10  </li>
  <li>stride for both would be 10  </li>
  <li>so the convolution filters apply to the same features only in different frames</li>
  </ul>
  
  <p>Basically I would need to specify an offset for the second conv filter. Is that possible?
  On the Caffe website they speak only about a zero padding, but for an offset I would need a negative padding.</p>
  
  <p>Is something like this possible?</p>
  
  <pre><code>layer {
    name: "conv2"
    type: "Convolution"
    bottom: "data"
    top: "conv2"
    param {
      lr_mult: 1
      decay_mult: 1
    }
    param {
      lr_mult: 2
      decay_mult: 0
    }
    convolution_param {
      num_output: 90
      kernel_h: 1
      kernel_w: 5
      pad_h: 0
      pad_w: -5   
      stride: 10
      weight_filler {
        type: "gaussian"
        std: 0.01
      }
      bias_filler {
        type: "constant"
        value: 0
      }
    }
  }
  </code></pre>