Abstract Knowledge distillation transfers knowledge from the teacher network to the student
one, with the goal of greatly improving the performance of the student network. Previous …

Deep neural models, in recent years, have been successful in almost every field, even
solving the most complex problem statements. However, these models are huge in size with …

For years, the YOLO series has been the de facto industry-level standard for efficient object
detection. The YOLO community has prospered overwhelmingly to enrich its use in a …

State-of-the-art distillation methods are mainly based on distilling deep features from
intermediate layers, while the significance of logit distillation is greatly overlooked. To …

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

Abstract Knowledge distillation has been applied to various tasks successfully. The current
distillation algorithm usually improves students' performance by imitating the output of the …

In this paper, an ill-posed problem of multiple adverse weather removal is investigated. Our
goal is to train a model with a'unified'architecture and only one set of pretrained weights that …

In recent years, deep neural networks have been successful in both industry and academia,
especially for computer vision tasks. The great success of deep learning is mainly due to its …

In this report, we present a fast and accurate object detection method dubbed DAMO-YOLO,
which achieves higher performance than the state-of-the-art YOLO series. DAMO-YOLO is …

摘要视觉目标检测旨在定位和识别图像中存在的物体, 属于计算机视觉领域的经典任务之一,
也是许多计算机视觉任务的前提与基础, 在自动驾驶, 视频监控等领域具有重要的应用价值 …