Fine-tuning visual models has been widely shown promising performance on many
downstream visual tasks. With the surprising development of pre-trained visual foundation …

Object detection is a fundamental computer vision task that simultaneously predicts the
category and localization of the targets of interest. Recently one-stage (also termed “dense”) …

Object detection (OD) is a crucial computer vision task that has seen the development of
many algorithms and models over the years. While the performance of current OD models …

Object detection is a fundamental yet challenging task in computer vision. Despite the great
strides made over recent years, modern detectors may still produce unsatisfactory …

3D object detection from multiple image views is a fundamental and challenging task for
visual scene understanding. Owing to its low cost and high efficiency, multi-view 3D object …

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 …

Despite the prominent success of general object detection, the performance and efficiency of
Small Object Detection (SOD) are still unsatisfactory. Unlike existing works that struggle to …

Although Deep neural networks (DNNs) have shown a strong capacity to solve large-scale
problems in many areas, such DNNs are hard to be deployed in real-world systems due to …

Abstract Knowledge distillation (KD) has shown potential for learning compact models in
dense object detection. However, the commonly used softmax-based distillation ignores the …

Object detection via inaccurate bounding box supervision has boosted a broad interest due
to the expensive high-quality annotation data or the occasional inevitability of low annotation …