Trident-YOLO: Improving the precision and speed of mobile device object detection

[1]  Trevor Darrell,et al.  Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Hong-Yuan Mark Liao,et al.  YOLOv4: Optimal Speed and Accuracy of Object Detection , 2020, ArXiv.

[3]  Ali Farhadi,et al.  You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[4]  Yunhong Wang,et al.  Receptive Field Block Net for Accurate and Fast Object Detection , 2017, ECCV.

[5]  Rachel Huang,et al.  YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers , 2018, 2018 IEEE International Conference on Big Data (Big Data).

[6]  Michael S. Bernstein,et al.  ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.

[7]  Jie Gu,et al.  Progressive Sparse Local Attention for Video Object Detection , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[8]  Hang Xu,et al.  Auto-FPN: Automatic Network Architecture Adaptation for Object Detection Beyond Classification , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[9]  Jun-Wei Hsieh,et al.  CSPNet: A New Backbone that can Enhance Learning Capability of CNN , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[10]  David A. McAllester,et al.  Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Vishal M. Patel,et al.  MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Junying Chen,et al.  UP-DETR: Unsupervised Pre-training for Object Detection with Transformers , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Jian Sun,et al.  Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition , 2015, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[15]  Quoc V. Le,et al.  NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Quoc V. Le,et al.  Searching for MobileNetV3 , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[17]  Quoc V. Le,et al.  EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks , 2019, ICML.

[18]  Ross B. Girshick,et al.  Fast R-CNN , 2015, 1504.08083.

[19]  Bo Chen,et al.  MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.

[20]  Raquel Urtasun,et al.  Understanding the Effective Receptive Field in Deep Convolutional Neural Networks , 2016, NIPS.

[21]  Zhaoxiang Zhang,et al.  Scale-Aware Trident Networks for Object Detection , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[22]  Quoc V. Le,et al.  EfficientDet: Scalable and Efficient Object Detection , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  Wei Liu,et al.  SSD: Single Shot MultiBox Detector , 2015, ECCV.

[24]  Vinay P. Namboodiri,et al.  HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[25]  Chien-Yao Wang,et al.  Scaled-YOLOv4: Scaling Cross Stage Partial Network , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  Hyuk-Jae Lee,et al.  Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[27]  Shiming Xiang,et al.  AugFPN: Improving Multi-Scale Feature Learning for Object Detection , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[28]  Yi Jiang,et al.  Sparse R-CNN: End-to-End Object Detection with Learnable Proposals , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[29]  Ali Farhadi,et al.  YOLO9000: Better, Faster, Stronger , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[30]  Mark Sandler,et al.  MobileNetV2: Inverted Residuals and Linear Bottlenecks , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[31]  Kaiming He,et al.  Feature Pyramid Networks for Object Detection , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[32]  François Chollet,et al.  Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[33]  Yanzhi Wang,et al.  YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design , 2020, AAAI.

[34]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[35]  Kaiming He,et al.  Focal Loss for Dense Object Detection , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).