Fusion tracking based on visible and thermal infrared images can boost tracking
performance under adverse challenging conditions, such as low illumination and bad …

End-to-end scene text spotting, which aims to read the text in natural images, has garnered
significant attention in recent years. However, recent state-of-the-art methods usually …

Lung granuloma is a very common lung disease, and its specific diagnosis is important for
determining the exact cause of the disease as well as the prognosis of the patient. And, an …

Synthetic aperture radar (SAR) is essential in actively acquiring information for Earth
observation. SAR Automatic Target Recognition (ATR) focuses on detecting and classifying …

Cytology inspection is a basic examination for the prevention of cervical cancer, which is still
done manually and is a labor-intensive and time-consuming process with high inter …

We propose a new approach, Synthetic Optimized Layout with Instance Detection (SOLID),
to pretrain object detectors with synthetic images. Our" SOLID" approach consists of two …

Long-term monitoring and recognition of underwater organism objects are of great
significance in marine ecology, fisheries science and many other disciplines. Traditional …

Few-shot object detection (FSOD) aims to address the challenge of requiring a substantial
number of annotations for training in conventional object detection, which is very labor …

Action tube detection is a challenging task as it requires not only to locate action instances in
each frame, but also link them in time. Existing action tube detection methods often employ …

Large-scale pre-training followed by downstream fine-tuning is an effective solution for
transferring deep-learning-based models. Since finetuning all possible pre-trained models is …