most citedMMDetection: Open MMLab Detection Toolbox and Benchmark

794 citations · 1.6k across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV202124 cited

Towards Balanced Learning for Instance Recognition

Jiangmiao Pang, Kai Chen, Qi Li +5

Instance recognition is rapidly advanced along with the developments of various deep convolutional neural networks. Compared to the architectures of networks, the training process,…

cs.CV2021197 cited

K-Net: Towards Unified Image Segmentation

Wenwei Zhang, Jiangmiao Pang, Kai Chen +1

Semantic, instance, and panoptic segmentations have been addressed using different and specialized frameworks despite their underlying connections. This paper presents a unified, s…

cs.CV2021

FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection

Tai Wang, Xinge Zhu, Jiangmiao Pang +1

Monocular 3D object detection is an important task for autonomous driving considering its advantage of low cost. It is much more challenging than conventional 2D cases due to its i…

cs.CV2019

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…

cs.CV2019794 cited

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…

cs.CV2019138 cited

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…