One-Shot Aggregation
One-Shot Aggregation
**One-Shot Aggregation** is an image model block that is an alternative to [Dense Blocks](https://paperswithcode.com/method/dense-block), by aggregating intermediate features. It is proposed as part of the [VoVNet](https://paperswithcode.com/method/vovnet) architecture. Each [convolution](https://paperswithcode.com/method/convolution) layer is connected by two-way connection. One way is connected to the subsequent layer to produce the feature with a larger receptive field while the other way is aggregated only once into the final output feature map. The difference with [DenseNet](https://paperswithcode.com/method/densenet) is that the output of each layer is not routed to all subsequent intermediate layers which makes the input size of intermediate layers constant.
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
https://paperswithcode.com/paper/an-energy-and-gpu-computation-efficient
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection