Video object detection has been an important yet challenging topic in computer vision. Traditional methods mainly focus on designing the image-level or box-level feature propagation strategies to exploit temporal information. This paper argues that with a more effective and efficient framework, video detectors can gain improvement terms of both accuracy speed. For this purpose, studies object-l...

Weakly Supervised Object Detection (WSOD) is a task that detects objects in an image using model trained only on image-level annotations. Current state-of-the-art models benefit from self-supervised instance-level supervision, but since weak supervision does not include count or location information, the most common “argmax” labeling method often ignores many instances of objects. To alleviate ...