Whole-body pose estimation localizes the human body, hand, face, and foot keypoints in an
image. This task is challenging due to multi-scale body parts, fine-grained localization for …

Abstract Knowledge distillation has been applied to image classification successfully.
However, object detection is much more sophisticated and most knowledge distillation …

Abstract Knowledge distillation is a widely used paradigm for inheriting information from a
complicated teacher network to a compact student network and maintaining the strong …

In recent years, knowledge distillation has been proved to be an effective solution for model
compression. This approach can make lightweight student models acquire the knowledge …

Traditional object detectors are ill-equipped for incremental learning. However, fine-tuning
directly on a well-trained detection model with only new data will lead to catastrophic …

Abstract Knowledge distillation (KD) has witnessed its powerful capability in learning
compact models in object detection. Previous KD methods for object detection mostly focus …

Abstract Knowledge distillation (KD) is a widely-used technique to train compact models in
object detection. However, there is still a lack of study on how to distill between …

In recent years, large-scale deep models have achieved great success, but the huge
computational complexity and massive storage requirements make it a great challenge to …

Abstract Knowledge Distillation (KD) is a widely-used technology to inherit information from
cumbersome teacher models to compact student models, consequently realizing model …

Lightweight object detector is currently gaining more and more popularity in remote sensing.
In general, it is hard for lightweight detectors to achieve competitive performance compared …