Video object detection is challenging because objects that are easily
detected in one frame may be difficult to detect in another frame within the
same clip. Recently, there have been major advances for doing object detection
in a single image. These methods typically contain three phases: (i) object
proposal generation (ii) object classification and (iii) post-processing. We
propose a modification of the post-processing phase that uses high-scoring
object detections from nearby frames to boost scores of weaker detections
within the same clip. We show that our method obtains superior results to
state-of-the-art single image object detection techniques. Our method placed
3rd in the video object detection (VID) task of the ImageNet Large Scale Visual
Recognition Challenge 2015 (ILSVRC2015).

本文将视觉目标检测中的三个阶段进行了修改，采用了从相邻帧提取高得分目标检测的方法来增强同一剪辑中弱目标检测的得分，并获得了比现有技术更好的结果。该方法在 ImageNet 大规模视觉识别挑战赛 2015 年的视频目标检测（VID）任务中取得了第三名。