暂无分享,去创建一个
Ying Wu | Xu Zou | Xiangyun Zhao | Ying Wu | Xiangyun Zhao | Xu Zou
[1] Hong Yu,et al. Meta Networks , 2017, ICML.
[2] Deva Ramanan,et al. Meta-Learning to Detect Rare Objects , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[3] Kaiming He,et al. Feature Pyramid Networks for Object Detection , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[5] Yi Li,et al. R-FCN: Object Detection via Region-based Fully Convolutional Networks , 2016, NIPS.
[6] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[7] Bernt Schiele,et al. Learning Deep Representations of Fine-Grained Visual Descriptions , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Nuno Vasconcelos,et al. Cascade R-CNN: Delving Into High Quality Object Detection , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[9] Yafeng Yang,et al. MNN: A Universal and Efficient Inference Engine , 2020, MLSys.
[10] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[11] Christoph H. Lampert,et al. Learning to detect unseen object classes by between-class attribute transfer , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[12] Ali Farhadi,et al. YOLO9000: Better, Faster, Stronger , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Kavita Bala,et al. Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[16] Anton van den Hengel,et al. Less is More: Zero-Shot Learning from Online Textual Documents with Noise Suppression , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Yoshua Bengio,et al. MetaGAN: An Adversarial Approach to Few-Shot Learning , 2018, NeurIPS.
[18] Oriol Vinyals,et al. Matching Networks for One Shot Learning , 2016, NIPS.
[19] Christoph H. Lampert,et al. Attribute-Based Classification for Zero-Shot Visual Object Categorization , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[20] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] Tsendsuren Munkhdalai,et al. Rapid Adaptation with Conditionally Shifted Neurons , 2017, ICML.
[22] Ahmed M. Elgammal,et al. Link the Head to the "Beak": Zero Shot Learning from Noisy Text Description at Part Precision , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Ali Farhadi,et al. You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Ali Farhadi,et al. YOLOv3: An Incremental Improvement , 2018, ArXiv.
[25] Venkatesh Saligrama,et al. Zero Shot Detection , 2018, IEEE Transactions on Circuits and Systems for Video Technology.
[26] Xin Wang,et al. Few-Shot Object Detection via Feature Reweighting , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[27] Kaiming He,et al. Focal Loss for Dense Object Detection , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[28] Tao Xiang,et al. Incremental Few-Shot Object Detection , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Venkatesh Saligrama,et al. Don’t Even Look Once: Synthesizing Features for Zero-Shot Detection , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Bharath Hariharan,et al. Low-Shot Visual Recognition by Shrinking and Hallucinating Features , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[31] Rama Chellappa,et al. Zero-Shot Object Detection , 2018, ECCV.
[32] Ying Wu,et al. Recognizing Part Attributes With Insufficient Data , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[33] Ross B. Girshick,et al. Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[34] Sharath Pankanti,et al. RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Hwann-Tzong Chen,et al. One-Shot Object Detection with Co-Attention and Co-Excitation , 2019, NeurIPS.
[36] Ying Wu,et al. Object Detection with a Unified Label Space from Multiple Datasets , 2020, ECCV.
[37] Raquel Urtasun,et al. Few-Shot Learning Through an Information Retrieval Lens , 2017, NIPS.
[38] Renaud Marlet,et al. Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild , 2020, ECCV.
[39] Lina Yao,et al. Zero-Shot Object Detection with Textual Descriptions , 2019, AAAI.
[40] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[41] Wei Liu,et al. SSD: Single Shot MultiBox Detector , 2015, ECCV.
[42] Ross B. Girshick,et al. Fast R-CNN , 2015, 1504.08083.
[43] Cordelia Schmid,et al. Label-Embedding for Image Classification , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Hugo Larochelle,et al. Optimization as a Model for Few-Shot Learning , 2016, ICLR.
[45] Hao Chen,et al. LSTD: A Low-Shot Transfer Detector for Object Detection , 2018, AAAI.
[46] Trevor Darrell,et al. Frustratingly Simple Few-Shot Object Detection , 2020, ICML.
[47] Rogério Schmidt Feris,et al. A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection , 2016, ECCV.
[48] Alexandre Lacoste,et al. TADAM: Task dependent adaptive metric for improved few-shot learning , 2018, NeurIPS.
[49] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[50] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[51] Xiaodan Liang,et al. Meta R-CNN: Towards General Solver for Instance-Level Low-Shot Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[52] Michael McCloskey,et al. Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem , 1989 .
[53] Luc Van Gool,et al. The Pascal Visual Object Classes Challenge: A Retrospective , 2014, International Journal of Computer Vision.
[54] Yichen Wei,et al. Pseudo Mask Augmented Object Detection , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[55] Yu-Wing Tai,et al. Few-Shot Object Detection With Attention-RPN and Multi-Relation Detector , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Babak Saleh,et al. Write a Classifier: Zero-Shot Learning Using Purely Textual Descriptions , 2013, 2013 IEEE International Conference on Computer Vision.