Despite the continued successes of computationally efficient deep neural network architectures for video object detection, performance continually arrives at great trilemma speed versus accuracy computational resources (pick two). Current attempts to exploit temporal information in data overcome this are bottlenecked by state art detection models. This work presents motion vector extrapolation ...