Jul 15, 2019 · In this work, we argue that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection.

In this work, we ar- gue that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection.

SELSA aggregates full-sequence level information of videos while keeping a simple and clean pipeline. It achieves 82.69 mAP with ResNet-101 on ImageNet VID ...

In this work, we ar- gue that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection.

This work argues that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection, ...

In this work, we argue that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection. To ...

Simultaneously, it provides a comparative reference for developing flying bird object detection algorithms in surveillance videos utilizing the dataset ...

In this work, we argue that aggregating features in the whole sequence level will lead to more discriminative and robust features for video object detection. To ...

Video Object Detection. Highlighting mentions of paper "Sequence Level Semantics Aggregation for Video Object Detection" ×. Video Object Detection on ImageNet ...

Multi-object tracking is crucial for scene understanding from video. • End Goal: Apply tracking to videos of surgeons performing open surgery to assess ...