  We tackle the problem of video object codetection by leveraging the weak
semantic constraint implied by sentences that describe the video content.
Unlike most existing work that focuses on codetecting large objects which are
usually salient both in size and appearance, we can codetect objects that are
small or medium sized. Our method assumes no human pose or depth information
such as is required by the most recent state-of-the-art method. We employ weak
semantic constraint on the codetection process by pairing the video with
sentences. Although the semantic information is usually simple and weak, it can
greatly boost the performance of our codetection framework by reducing the
search space of the hypothesized object detections. Our experiment demonstrates
an average IoU score of 0.423 on a new challenging dataset which contains 15
object classes and 150 videos with 12,509 frames in total, and an average IoU
score of 0.373 on a subset of an existing dataset, originally intended for
activity recognition, which contains 5 object classes and 75 videos with 8,854
frames in total.
