The document discusses several approaches for video object detection including flow-guided feature aggregation, deep feature flow, fully motion-aware networks, and tracklet-conditioned detection. It provides details on how each approach uses optical flow or tracking to aggregate or calibrate features over time. It also includes a table comparing several state-of-the-art video object detection methods based on metrics like mAP and frames per second.