Introduction
Recently, symmetric positive definitive (SPD) matrix-based visual representation methods have shown promising performance in various applications such as fine-grained image classification, person re-identification and ImageNet classification. This page keeps track of the recent advances in SPD matrix-based visual representation methods. Kindly refer to the contact section if you have any queries or sugesstions, and interested to add your method in the listings.
Workshops and tutorials on SPD representation
Tutorial on Higher-order Statistical Modeling based Deep Convolutional Neural Networks
- by Peihua Li, Wangmeng Zuo, Qilong Wang
- at Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2018
Tutorial on Second- and Higher-order Representations in Computer Vision
- by Piotr Koniusz, Mehrtash Harandi, Lei Wang, Ruiping Wang
- at International Conference on Computer Vision (ICCV), 2019
Selective SPD representation methods
Bilinear CNNs for Fine-grained Visual Recognition
- by Tsung-Yu Lin, Aruni RoyChowdhury, Subhransu Maji
- at International Conference on Computer Vision (ICCV), 2015
Compact Bilinear Pooling
- by Yang Gao, Oscar Beijbom, Ning Zhang, Trevor Darrell
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Kernel Pooling for Convolutional Neural Networks
- by Yin Cui, Feng Zhou, Jiang Wang, Xiao Liu, Yuanqing Lin, Serge Belongie
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Low-rank Bilinear Pooling for Fine-Grained Classification
- by Shu Kong, Charless Fowlkes
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Is Second-order Information Helpful for Large-scale Visual Recognition?
- by Peihua Li, Jiangtao Xie, Qilong Wang, Wangmeng Zuo
- at International Conference on Computer Vision (ICCV), 2017
Improved Bilinear Pooling with CNNs
- by Tsung-Yu Lin, Subhransu Maji
- at British Machine Vision Conference (BMVC), 2017
Factorized Bilinear Models for Image Recognition
- by Yanghao Li, Naiyan Wang, Jiaying Liu, Xiaodi Hou
- at International Conference on Computer Vision (ICCV), 2017
G2DeNet: Global Gaussian Distribution Embedding Network and Its Application to Visual Recognition
- by Qilong Wang, Peihua Li, Lei Zhang
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization
- by Peihua Li, Jiangtao Xie, Qilong Wang, Zilin Gao
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition
- by Chaojian Yu, Xinyi Zhao, Qi Zheng, Peng Zhang, Xinge You
- at European Conference on Computer Vision (ECCV), 2018
Statistically-motivated Second-order Pooling
- by Kaicheng Yu, Mathieu Salzmann
- at European Conference on Computer Vision (ECCV), 2018
DeepKSPD: learning kernel-matrix-based SPD representation for fine-grained image recognition
- by Melih Engin, Lei Wang, Luping Zhou, Xinwang Liu
- at European Conference on Computer Vision (ECCV), 2018
Second-order Democratic Aggregation
- by Tsung-Yu Lin, Subhransu Maji, Piotr Koniusz
- at European Conference on Computer Vision (ECCV), 2018
Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks
- by Qilong Wang, Zilin Gao, Jiangtao Xie, Wangmeng Zuo and Peihua Li
- at Advances in Neural Information Processing Systems (NIPS), 2018
Local Temporal Bilinear Pooling for Fine-Grained Action Parsing
- by Yan Zhang, Siyu Tang, Krikamol Muandet, Christian Jarvers, Heiko Neumann
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Global Second-order Pooling Convolutional Networks
- by Zilin Gao, Jiangtao Xie, Qilong Wang, Peihua Li
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Deep Global Generalized Gaussian Networks
- by Qilong Wang, Peihua Li, Qinghua Hu, Pengfei Zhu, Wangmeng Zuo.
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Second-order Attention Network for Single Image Super-Resolution
- by Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, Lei Zhang
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Low-Rank Pairwise Alignment Bilinear Network For Few-Shot Fine-Grained Image Classification
- by Huaxi Huang, Junjie Zhang, Jian Zhang, Jingsong Xu, Qiang Wu
- at arXiv:1908.01313v1, 2019
Compact Approximation for Polynomial of Covariance Feature
- by Yusuke Mukuta, Tatsuaki Machida, Tatsuya Harada
- at arXiv:1906.01851, 2019.
Learning Neural Bag-of-Matrix-Summarization with Riemannian Network
- by Hong Liu, Jie Li, Rongrong Ji, Yongjian Wu
- at AAAI Conference on Artificial Intelligence (AAAI), 2019
Fine-Grained Classification via Hierarchical Bilinear Pooling With Aggregated Slack Mask
- by Min Tan, Guijun Wang, Jian Zhou, Zhiyou Peng, Meilian Zheng
- at IEEE Access, Volume 7, pages 117944-117953, 2019
Learning Deep Bilinear Transformation for Fine-grained Image Representation
- by Heliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo
- at Conference on Neural Information Processing Systems (NIPS), 2019
Applications of SPD representation
Fundamental Research
Higher-Order Occurrence Pooling for Bags-of-Words: Visual Concept Detection
- by Piotr Koniusz, Fei Yan, Philippe-Henri Gosselin, Krystian Mikolajczyk
- at IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 39, No. 2, Pages 313-326, Feb. 2017
A Deeper Look at Power Normalizations
- by Piotr Koniusz, Hongguang Zhang, Fatih Porikli
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2018
A Robust Distance Measure for Similarity-Based Classification on the SPD Manifold
- by Zhi Gao, Yuwei Wu, Mehrtash Tafazzoli Harandi, Yunde Jia
- at IEEE Transactions on Neural Networks and Learning Systems, 2019
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
- by Qilong Wang, Liyong Zhang, Banggu Wu, Dongwei Ren, P. Li, W. Zuo, Q. Hu
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Revisiting Bilinear Pooling: A Coding Perspective
- by Z. Gao, Yuwei Wu, Xiaoxun Zhang, Jindou Dai, Y. Jia, M. Harandi
- at AAAI Conference on Artificial Intelligence, 2020
Power Normalizations in Fine-grained Image, Few-shot Image and Graph Classification
- by Piotr Koniusz and Hongguang Zhang
- at IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Fine-grained/Texture image classification
Bilinear CNNs for Fine-grained Visual Recognition
- by Tsung-Yu Lin, Aruni RoyChowdhury, Subhransu Maji
- at International Conference on Computer Vision (ICCV), 2015
Compact Bilinear Pooling
- by Yang Gao, Oscar Beijbom, Ning Zhang, Trevor Darrell
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Sparse Coding for Third-order Super-symmetric Tensor Descriptors with Application to Texture Recognition
- by Piotr Koniusz, Anoop Cherian
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Kernel Pooling for Convolutional Neural Networks
- by Yin Cui, Feng Zhou, Jiang Wang, Xiao Liu, Yuanqing Lin, Serge Belongie
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Low-rank Bilinear Pooling for Fine-Grained Classification
- by Shu Kong, Charless Fowlkes
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Improved Bilinear Pooling with CNNs
- by Tsung-Yu Lin, Subhransu Maji
- at British Machine Vision Conference (BMVC), 2017
Factorized Bilinear Models for Image Recognition
- by Yanghao Li, Naiyan Wang, Jiaying Liu, Xiaodi Hou
- at International Conference on Computer Vision (ICCV), 2017
G2DeNet: Global Gaussian Distribution Embedding Network and Its Application to Visual Recognition
- by Qilong Wang, Peihua Li, Lei Zhang
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Where to Focus: Deep Attention-based Spatially Recurrent Bilinear Networks forFine-Grained Visual Recognition
- by Lin Wu, Yang Wang
- at arXiv:1709.05769, 2017
Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization
- by Peihua Li, Jiangtao Xie, Qilong Wang, Zilin Gao
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition
- by Chaojian Yu, Xinyi Zhao, Qi Zheng, Peng Zhang, Xinge You
- at European Conference on Computer Vision (ECCV), 2018
Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification
- by Xing Wei, Yue Zhang, Yihong Gong, Jiawei Zhang, Nanning Zheng
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Statistically-motivated Second-order Pooling
- by Kaicheng Yu, Mathieu Salzmann
- at European Conference on Computer Vision (ECCV), 2018
DeepKSPD: learning kernel-matrix-based SPD representation for fine-grained image recognition
- by Melih Engin, Lei Wang, Luping Zhou, Xinwang Liu
- at European Conference on Computer Vision (ECCV), 2018
Second-order Democratic Aggregation
- by Tsung-Yu Lin, Subhransu Maji, Piotr Koniusz
- at European Conference on Computer Vision (ECCV), 2018
Fine-Grained Image Classification With Gaussian Mixture Layer
- by Jingyun Liang, Jinlin Guo, Xin Liu, Songyang Lao
- at IEEE Access, Volume 6, pages 53356-53367, 2018
Learning a Robust Representation via a Deep Network on Symmetric Positive Definite Manifolds
- by Zhi Gao, Yuwei Wu, Xingyuan Bu, Yunde Jia
- at Pattern Recognition, Volume 92, Pages 1-12, 2019
Compact Approximation for Polynomial of Covariance Feature
- by Yusuke Mukuta, Tatsuaki Machida, Tatsuya Harada
- at arXiv:1906.01851, 2019.
Fine-Grained Classification via Hierarchical Bilinear Pooling With Aggregated Slack Mask
- by Min Tan, Guijun Wang, Jian Zhou, Zhiyou Peng, Meilian Zheng
- at IEEE Access, Volume 7, pages 117944-117953, 2019
Learning Deep Bilinear Transformation for Fine-grained Image Representation
- by Heliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo
- at Conference on Neural Information Processing Systems (NIPS), 2019
ReDro: Efficiently Learning Large-Sized SPD Visual Representation
- by S. Rahman, Lei Wang, Changming Sun, L. Zhou
- at European Conference on Computer Vision (ECCV), 2020
ImageNet/Generic image classification
Is Second-order Information Helpful for Large-scale Visual Recognition?
- by Peihua Li, Jiangtao Xie, Qilong Wang, Wangmeng Zuo
- at International Conference on Computer Vision (ICCV), 2017
Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization
- by Peihua Li, Jiangtao Xie, Qilong Wang, Zilin Gao
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks
- by Qilong Wang, Zilin Gao, Jiangtao Xie, Wangmeng Zuo and Peihua Li
- at Advances in Neural Information Processing Systems (NIPS), 2018
Global Second-order Pooling Convolutional Networks
- by Zilin Gao, Jiangtao Xie, Qilong Wang, Peihua Li
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Deep Global Generalized Gaussian Networks
- by Qilong Wang, Peihua Li, Qinghua Hu, Pengfei Zhu, Wangmeng Zuo
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Action parsing/Temporal modelling
Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons
- by Piotr Koniusz, Anoop Cherian, Fatih Porikli
- at European Conference on Computer Vision (ECCV), 2016
Higher-Order Pooling of CNN Features via Kernel Linearization for Action Recognition
- by Anoop Cherian, Piotr Koniusz, Stephen Gould
- at Winter Conference on Applications of Computer Vision (WACV), 2017
Local Temporal Bilinear Pooling for Fine-Grained Action Parsing
- by Yan Zhang, Siyu Tang, Krikamol Muandet, Christian Jarvers, Heiko Neumann
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Approximated Bilinear Modules for Temporal Modeling
- by Xinqi Zhu, Chang Xu, Langwen Hui, Cewu Lu, Dacheng Tao
- at International Conference on Computer Vision (ICCV), 2019
Tensor Representations for Action Recognition
- by Piotr Koniusz, Lei Wang, Anoop Cherian
- at IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Person Re-indentification
Second-Order Non-Local Attention Networks for Person Re-Identification
- by Bryan (Ning) Xia, Yuan Gong, Yizhe Zhang, Christian Poellabauer
- at International Conference on Computer Vision (ICCV), 2019
Mixed High-Order Attention Network for Person Re-Identification
- by Binghui Chen, Weihong Deng, Jiani Hu
- at International Conference on Computer Vision (ICCV), 2019
High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification
- by G. Wang, S. Yang, Huanyu Liu, Z. Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, J. Sun
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Second-order Camera-aware Color Transformation for Cross-domain Person Re-identification
- by Wangmeng Xiang, Hongwei Yong, Jianqiang Huang, Xian-Sheng Hua, Lei Zhang
- at Asian Conference on Computer Vision (ACCV), 2020
Domain Adaptation
Domain Adaptation by Mixture of Alignments of Second- or Higher-Order Scatter Tensors
- by Piotr Koniusz, Yusuf Tas, Fatih Porikli
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Museum Exhibit Identification Challenge for Domain Adaptation and Beyond
- by Piotr Koniusz, Yusuf Tas, Hongguang Zhang, Mehrtash Harandi, Fatih Porikli, Rui Zhang
- at European Conference on Computer Vision (ECCV), 2018
Domain Adaptation Using Riemannian Geometry of SPD Matrices
- by Gal Maman, Or Yair, Danny Eytan, Ronen Talmon
- at International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
Few-shot Learning
Power Normalizing Second-Order Similarity Network for Few-Shot Learning
- by Hongguang Zhang, Piotr Koniusz
- at Winter Conference on Applications of Computer Vision (WACV), 2018
Few-Shot Learning via Saliency-guided Hallucination of Samples
- by Hongguang Zhang, Jing Zhang, Piotr Koniusz
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Few-Shot Object Detection by Second-order Pooling
- by Shan Zhang, Dawei Luo, Lei Wang
- at Asian Conference on Computer Vision (ACCV), 2020
Few-shot Action Recognition with Permutation-invariant Attention
- by Hongguang Zhang, Li Zhang, Xiaojuan Qi, Hongdong Li, Philip Torr, Piotr Koniusz
- at European Conference on Computer Vision (ECCV), 2020
Adaptive Subspaces for Few-Shot Learning
- by Christian Simon, Piotr Koniusz, Richard Nock, Mehrtash Harandi
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Others
RAID-G: Robust Estimation of Approximate Infinite Dimensional Gaussian with Application to Material Recognition
- by Qilong Wang, Peihua Li1, Wangmeng Zuo, Lei Zhang
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2016
A Neural Network Based on SPD Manifold Learning for Skeleton-Based Hand Gesture Recognition
- by Xuan Son Nguyen, Luc Brun, Olivier Lezoray, Sebastien Bougleux
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Second-Order Attention Network for Single Image Super-Resolution
- by Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, Lei Zhang
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Bilinear Attention Networks for Person Retrieval
- by Pengfei Fang, Jieming Zhou, Soumava Kumar Roy, Lars Petersson, Mehrtash Harandi
- at International Conference on Computer Vision (ICCV), 2019
Factorized Higher-Order CNNs with an Application to Spatio-Temporal Emotion Estimation
- by Jean Kossaifi, Antoine Toisoul, Adrian Bulat, Yannis Panagakis, Timothy M. Hospedales, M. Pantic
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2020
DOA-GAN: Dual-Order Attentive Generative Adversarial Network for Image Copy-move Forgery Detection and Localization
- by Ashraful Islam, Chengjiang Long, A. Basharat, A. Hoogs
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Visual-Semantic Matching by Exploring High-Order Attention and Distraction
- by Yongzhi Li, D. Zhang, Y. Mu
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Second Order enhanced Multi-glimpse Attention in Visual Question Answering
- by Qiang Sun, Binghui Xie, Yanwei Fu
- at Asian Conference on Computer Vision (ACCV), 2020
SOFA-Net: Second-Order and First-order Attention Network for Crowd Counting
- by Haoran Duan, Shidong Wang, Yu Guan
- at British Machine Vision Conference (BMVC), 2020
BARNet: Bilinear Attention Network with Adaptive Receptive Field for Surgical Instrument Segmentation
- by Zhen-Liang Ni, Guibin Bian, G. Wang, Xiao-Hu Zhou, Zengguang Hou, Xiaoliang Xie, Zhuguo Li, Yu-Han Wang
- at International Joint Conference on Artificial Intelligence (IJCAI), 2020
Non-Local Neural Networks with Grouped Bilinear Attentional Transforms
- by L. Chi, Ze-Huan Yuan, Y. Mu, C. Wang
- at International Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Analysis of existing methods and their performance
Plese feel free to use sorting options and search box for efficient analysis of the existing SPD representation based methods and their results.
| Summary of method | Performace across datasets (in %) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Year | Method | Backbone Model | Classifier | Input Size | DA | Optimizer | Feature Size | CUB | Airplane | Cars | MIT | DTD | Food-101 | ImageNet |
| 2015 | Bilinear CNN | VGG-M/VGG-16 | SVM | 448X448 | Flip | SGD | 262k | 84.1 | 84.1 | 91.3 | -- | -- | -- | -- |
| 2016 | RAID-G | VGG19 | SVM | 224X224 | -- | -- | -- | 84.0 | -- | -- | -- | 76.4 | -- | -- |
| 2016 | Compact Bilinear | VGGM/VGG16 | SVM | 448X448 | -- | SGD | 10k | 84.0 | -- | -- | 73.4 | 67.7 | -- | -- |
| 2017 | Kernel Pooling | VGG16/ResNet50 | SVM | 448X448 | Flip, Crop | SGD | 12.8k/14.3k | 86.2 | 86.9 | 92.4 | -- | -- | 85.5 | -- |
| 2017 | Low-Rank Bilinear | VGG16/ResNet50 | SVM | 448X448 | Flip, Crop | SGD | 12.8k/14.3k | 84.2 | 87.3 | 90.9 | -- | 65.8 | -- | -- |
| 2017 | MPN-COV | VGG16/ResNet50 | SVM | 448X448 | Jitter | SGD | 32k | -- | -- | -- | -- | -- | -- | 78.8 |
| 2017 | Improved BCNN | VGGM/VGG16 | SVM | 448X448 | Flip | SGD | 262k | 85.8 | 88.5 | 92.0 | -- | -- | -- | -- |
| 2017 | Factorized bilinear | ResNet50 | SVM | 112X112 | Flip, Crop | SGD | 10M | 82.9 | -- | -- | -- | 67.8 | -- | 76.0 |
| 2017 | G2DeNet | VGG16 | SVM | 448X448 | Flip | SGD | 131k | 87.1 | 89.0 | 92.5 | -- | -- | -- | -- |
| 2017 | Recurrent Bilinear | VGG16 | SVM | 448X448 | Flip, Shift | SGD | 262k | 89.7 | 88.4 | 93.4 | -- | -- | -- | -- |
| 2018 | iSQRT-COV | AlexNet/ResNet101 | Softmax | 224X224 | Flip, Crop, Jitter | SGD | 32k | 88.7 | 91.4 | 93.3 | -- | -- | -- | 78.79 |
| 2018 | Grassmann Pooling | VGG16 | Softmax | 448X448 | Flip | SGD | 4k | 85.8 | 89.8 | 92.8 | -- | -- | 85.7 | -- |
| 2018 | Hierarchical Bilinear | VGG16 | Softmax | 448X448 | Flip, Crop | SGD | 8k | 87.1 | 90.3 | 93.7 | -- | -- | -- | -- |
| 2018 | SMSO Pooling | VGG16/ResNet50 | Softmax | 448X448 | Flip | SGD | 2k | 85.8 | -- | -- | 79.7 | 72.5 | -- | -- |
| 2018 | DeepKSPD | VGG16 | Softmax | 448X448 | Flip | Adam | 262k | 86.5 | 91.5 | 93.2 | 81.0 | -- | -- | -- |
| 2018 | SoDA | VGG16/ResNet50 | SVM | 448X448 | Flip | SGD | 8k/262k | 85.9 | 87.6 | 91.7 | 84.3 | 76.2 | -- | -- |
| 2018 | GM-SOP | ResNet18 | Softmax | 64X64 | Flip | SGD | 8k | -- | -- | -- | -- | -- | -- | 67.7* |
| 2018 | GMNet | VGG16/VGG19 | Softmax | random | Flip | SGD | 400k | 86.3 | 90.5 | 93.5 | -- | -- | -- | -- |
| 2020 | SOP+SC+SigmE | AlexNet/ResNet50 | Softmax | 224/336/448 | Flip | Adam | -- | -- | -- | -- | 86.3 | -- | 87.5 | -- |
| 2019 | SPD aggregation Network | VGG16 | Softmax | 224X224 | -- | SGD | 262k | 72.4 | 77.8 | -- | -- | 68.9 | -- | -- |
| 2019 | Global SoP | ResNet50 | Softmax | 224X224 | Flip | SGD | 2k/32k | -- | -- | -- | -- | -- | -- | 78.9* |
| 2019 | 3G-Net | ResNet50/ResNet101 | Softmax | 224X224 | Flip | SGD | 32k | -- | -- | -- | -- | -- | -- | 79.1* |
| 2019 | iPCCP-Net | ResNet50/ResNet101 | Softmax | 448X448 | Flip | SGD | 8k | 88.4 | 91.6 | 94.1 | -- | -- | -- | -- |
| 2019 | HBPASM | ResNet-34 | Softmax | 448X448 | Flip | SGD | 24k | 86.8 | 91.3 | 93.8 | -- | -- | -- | -- |
| 2019 | DBTNet | ResNet50/ResNet101 | Softmax | 448X448 | -- | SGD | 2k | 88.1 | 91.6 | 94.5 | -- | -- | -- | -- |
| 2020 | ReDro | VGG16/ResNet50 | Softmax | 448X448 | Flip | Adam | 262k | 84.3 | 89.2 | 92.2 | 84.0 | -- | -- | -- |
| 2020 | SOP+SC+Spec. MaxExp(F) | AlexNet/ResNet50 | Softmax | 224/336/448 | Flip | Adam | -- | -- | -- | -- | 86.8 | -- | 88.4 | 77.95 |
* - Produced with ImageNet-1k dataset while the others use ImageNet-2012 dataset.
Acknowledgements
This website uses images and code links that are shared by the original authors. Bootstarp 4 CSS library and jQuery 3.x were used for the development of this website.
Contact
For any queries and sugesstions you may directly contact at sr801@uowmail.edu.au or leiw@uow.edu.au. Also, please do not hesitate to contact us if you would like to add your method into the listing of SPD Archive.