892 citations · 3.1k across the 17 of their papers we have counts for
5 papers · 1 filter
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng +1
Currently, the neural network architecture design is mostly guided by the \emph{indirect} metric of computation complexity, i.e., FLOPs. However, the \emph{direct} metric, e.g., sp…
MetaAnchor: Learning to Detect Objects with Customized Anchors
Tong Yang, Xiangyu Zhang, Zeming Li +2
We propose a novel and flexible anchor mechanism named MetaAnchor for object detection frameworks. Unlike many previous detectors model anchors via a predefined manner, in MetaAnch…
CrowdHuman: A Benchmark for Detecting Human in a Crowd
Shuai Shao, Zijian Zhao, Boxun Li +4
Human detection has witnessed impressive progress in recent years. However, the occlusion issue of detecting human in highly crowded environments is far from solved. To make matter…
DetNet: A Backbone network for Object Detection
Zeming Li, Chao Peng, Gang Yu +3
Recent CNN based object detectors, no matter one-stage methods like YOLO, SSD, and RetinaNe or two-stage detectors like Faster R-CNN, R-FCN and FPN are usually trying to directly f…
ExFuse: Enhancing Feature Fusion for Semantic Segmentation
Zhenli Zhang, Xiangyu Zhang, Chao Peng +2
Modern semantic segmentation frameworks usually combine low-level and high-level features from pre-trained backbone convolutional models to boost performance. In this paper, we fir…