794 citations · 1.7k across the 31 of their papers we have counts for
7 papers · 1 filter
Side-Aware Boundary Localization for More Precise Object Detection
Jiaqi Wang, Wenwei Zhang, Yuhang Cao +6
Current object detection frameworks mainly rely on bounding box regression to localize objects. Despite the remarkable progress in recent years, the precision of bounding box regre…
MMDetection: Open MMLab Detection Toolbox and Benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang +22
We present MMDetection, an object detection toolbox that contains a rich set of object detection and instance segmentation methods as well as related components and modules. The to…
CARAFE: Content-Aware ReAssembly of FEatures
Jiaqi Wang, Kai Chen, Rui Xu +3
Feature upsampling is a key operation in a number of modern convolutional network architectures, e.g. feature pyramids. Its design is critical for dense prediction tasks such as ob…
Libra R-CNN: Towards Balanced Learning for Object Detection
Jiangmiao Pang, Kai Chen, Jianping Shi +3
Compared with model architectures, the training process, which is also crucial to the success of detectors, has received relatively less attention in object detection. In this work…
Prime Sample Attention in Object Detection
Yuhang Cao, Kai Chen, Chen Change Loy +1
It is a common paradigm in object detection frameworks to treat all samples equally and target at maximizing the performance on average. In this work, we revisit this paradigm thro…
Hybrid Task Cascade for Instance Segmentation
Kai Chen, Jiangmiao Pang, Jiaqi Wang +9
Cascade is a classic yet powerful architecture that has boosted performance on various tasks. However, how to introduce cascade to instance segmentation remains an open question. A…