Image Classification with the Fisher Vector: Theory and Practice

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

Distinctive Image Features from Scale-Invariant Keypoints

Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589

The pascal visual object classes (VOC) challenge

Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599

Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

Lazebnik, S., Schmid, C., & Ponce, J. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.68 · Cited by 7,916

The Pascal Visual Object Classes Challenge: A Retrospective

Everingham, M., Eslami, S. M. A., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-014-0733-5 · Cited by 7,139

Video Google: a text retrieval approach to object matching in videos

Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367

Visual categorization with bags of keypoints

Csurka, G. (2004) · Cited by 4,379

SUN database: Large-scale scene recognition from abbey to zoo

Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., & Torralba, A. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539970 · Cited by 3,283

Locality-constrained Linear Coding for image classification

Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., & Gong, Y. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5540018 · Cited by 3,100

Multimodal data fusion for sensitive scene localization

Moreira, D., Avila, S., Pérez, M., Moraes, D., Testoni, V., Junior, E. A. D. V., Goldenstein, S. K., & Rocha, A. D. R. (2018) · Information Fusion · doi:10.1016/j.inffus.2018.03.001 · Cited by 33

Bidirectional image-sentence retrieval by local and global deep matching

Ma, L., Jiang, W., Jie, Z., & Wang, X. (2019) · Neurocomputing · doi:10.1016/j.neucom.2018.11.089 · Cited by 33

Trespassing the Boundaries: Labeling Temporal Bounds for Object Interactions in Egocentric Video

Moltisanti, D., Wray, M., Mayol-Cuevas, W. W., & Damen, D. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.314 · Cited by 33

Fisher encoding of differential fast point feature histograms for partial 3D object retrieval

Savelonas, M. A., Pratikakis, I., & Sfikas, K. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.02.003 · Cited by 32

An online writer identification system using regression-based feature normalization and codebook descriptors

Venugopal, V., & Sundaram, S. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.11.038 · Cited by 32

MSN: Modality separation networks for RGB-D scene recognition

Xiong, Z., Yuan, Y., & Wang, Q. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.09.066 · Cited by 32

Scene image representation by foreground, background and hybrid features

Sitaula, C., Xiang, Y., Aryal, S., & Lu, X. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115285 · Cited by 32

A Comprehensive Study on Codebook-Based Feature Fusion for Gait Recognition

Khan, M. H., Farid, M. S., & Grzegorzek, M. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.12.001 · Cited by 32

3D point cloud descriptors: state-of-the-art

Han, X.-F., Feng, Z.-A., Sun, S., & Xiao, G. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10486-4 · Cited by 33

A Comprehensive Study of the Effect of Spatial Resolution and Color of Digital Images on Vehicle Classification

Hussain, K., Afifi, M., & Moussa, G. S. (2019) · IEEE transactions on intelligent transportation systems (Print) · doi:10.1109/tits.2018.2838117 · Cited by 24

Deep learning-based fusion networks with high-order attention mechanism for 3D object detection in autonomous driving scenarios

Jiang, H., Lu, Y., Zhang, D., Shi, Y., & Wang, J. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.111253 · Cited by 33

From categories to subcategories: Large-scale image classification with partial class label refinement

Ristin, M., Gall, J., Guillaumin, M., & Gool, L. V. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298619 · Cited by 31

Good Practices for Learning to Recognize Actions Using FV and VLAD

Wu, J., Zhang, Y., & Lin, W. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2493538 · Cited by 31

Motion keypoint trajectory and covariance descriptor for human action recognition

Yi, Y., & Wang, H.-L. (2018) · The Visual Computer · doi:10.1007/s00371-016-1345-6 · Cited by 32

Scale coding bag of deep features for human attribute and action recognition

Khan, F. S., van de Weijer, J., Anwer, R. M., Bagdanov, A. D., Felsberg, M., & Laaksonen, J. T. (2017) · Machine Vision and Applications · doi:10.1007/s00138-017-0871-1 · Cited by 31

Polyhedral Conic Classifiers for Visual Object Detection and Classification

Çevıkalp, H., & Triggs, B. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.438 · Cited by 31

Sparse Embedded $k$-Means Clustering

Liu, W., Shen, X., & Tsang, I. W.-H. (2017) · UTS ePRESS (University of Technology Sydney) · Cited by 31

Hyperlayer Bilinear Pooling with application to fine-grained categorization and image retrieval

Sun, Q., Wang, Q., Zhang, J., & Li, P. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.12.020 · Cited by 30

Second-Order Democratic Aggregation

Lin, T., Maji, S., & Koniusz, P. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01219-9_38 · Cited by 31

GestureVLAD: Combining Unsupervised Features Representation and Spatio-Temporal Aggregation for Doppler-Radar Gesture Recognition

Berenguer, A. D., Oveneke, M. C., Khalid, H.-U.-R., Alioscha‐Perez, M., Bourdoux, A., & Hichem Sahli, B. (2019) · IEEE Access · doi:10.1109/access.2019.2942305 · Cited by 30

Can a Hierarchical Classification of Sentinel-2 Data Improve Land Cover Mapping?

Waśniewski, A., Hościło, A., & Chmielewska, M. (2022) · Remote Sensing · doi:10.3390/rs14040989 · Cited by 34

CSPS: An Adaptive Pooling Method for Image Classification

Wang, J., Wang, W., Wang, R., & Gao, W. (2016) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2016.2544099 · Cited by 32

Exploring synonyms as context in zero-shot action recognition

Alexiou, I., Xiang, T., & Gong, S. (2016) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2016.7533149 · Cited by 31

In Defense of Word Embedding for Generic Text Representation

Lev, G., Klein, B., & Wolf, L. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-19581-0_3 · Cited by 30

Unsupervised Web Topic Detection Using A Ranked Clustering-Like Pattern Across Similarity Cascades

Pang, J., Jia, F., Zhang, C., Zhang, W., Huang, Q., & Yin, B. (2015) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2015.2425143 · Cited by 30

Towards effective codebookless model for image classification

Wang, Q., Li, P., Lei Zhang, A., & Zuo, W. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.03.004 · Cited by 30

Learning Dictionary of Discriminative Part Detectors for Image Categorization and Cosegmentation

Sun, J. Z., & Ponce, J. (2016) · International Journal of Computer Vision · doi:10.1007/s11263-016-0899-0 · Cited by 30

Modeling and Learning Distributed Word Representation with Metadata for Question Retrieval

Zhou, G., & Huang, J. X. (2017) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2017.2665625 · Cited by 30

Image-Specific Classification With Local and Global Discriminations

Zhang, C., Cheng, J., Li, C., & Tian, Q. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2748952 · Cited by 30

From Part to Whole

Ma, D., Gao, F., Bai, Y., Lou, Y., Wang, S., Huang, T., & Duan, L. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123325 · Cited by 30

Monitoring big process data of industrial plants with multiple operating modes based on Hadoop

Zhu, J., Yao, Y., Li, D., & Gao, F. (2018) · Journal of the Taiwan Institute of Chemical Engineers · doi:10.1016/j.jtice.2018.05.020 · Cited by 30

Depth‐based end‐to‐end deep network for human action recognition

Chaudhary, S., & Murala, S. (2018) · IET Computer Vision · doi:10.1049/iet-cvi.2018.5020 · Cited by 31

A clustering‐based feature selection framework for handwritten Indic script classification

Chatterjee, I., Ghosh, M., Singh, P. K., Sarkar, R., & Nasipuri, M. (2019) · Expert Systems · doi:10.1111/exsy.12459 · Cited by 30

Ship recognition based on Hu invariant moments and convolutional neural network for video surveillance

Ren, Y., Yang, J., Zhang, Q., & Guo, Z. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09574-2 · Cited by 31

Foreground Fisher Vector: Encoding Class-Relevant Foreground to Improve Image Classification

Pan, Y., Xia, Y., & Shen, D. G. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2908795 · Cited by 30

LOAD: Local orientation adaptive descriptor for texture and material classification

Qi, X., Zhao, G., Shen, L., Li, Q., & Pietikäinen, M. (2015) · Neurocomputing · doi:10.1016/j.neucom.2015.07.142 · Cited by 30

Beyond Explicit Codebook Generation: Visual Representation Using Implicitly Transferred Codebooks

Zhang, C., Cheng, J., Liu, J., Pang, J., Huang, Q., & Tian, Q. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2485783 · Cited by 29

Joint multi-feature spatial context for scene recognition in the semantic manifold

Song, X., Jiang, S., & Herranz, L. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298736 · Cited by 29

Bundled Local Features for Image Representation

Zhang, C., Sang, J., Zhu, G., & Tian, Q. (2017) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2694060 · Cited by 29

A Survey of Recent Advances in Texture Representation.

Liu, L., Chen, J., Fieguth, P., Zhao, G., Chellappa, R., & Pietikäinen, M. (2018) · Cited by 29

Shuffled ImageNet Banks for Video Event Detection and Search

Mettes, P., Koelma, D. C., & Snoek, C. G. M. (2020) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3377875 · Cited by 29

Discriminative Multi-View Dynamic Image Fusion for Cross-View 3-D Action Recognition

Wang, Y., Xiao, Y., Lu, J., Tan, B., Cao, Z., Zhang, Z., & Zhou, J. T. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3070179 · Cited by 29

Loop-Closure Detection Using Local Relative Orientation Matching

Ma, J., Ye, X., Zhou, H., Mei, X., & Fan, F. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3074520 · Cited by 29

Face mask recognition from audio: The MASC database and an overview on the mask challenge

Mohamed, M. M., Nessiem, M. A., Batliner, A. M., Bergler, C., Hantke, S., Schmitt, M., Baird, A., Mallol-Ragolta, A., Karas, V., Amiriparian, S., et al. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108361 · Cited by 38

Human action recognition based on multi-layer Fisher vector encoding method

Sekma, M., Mejdoub, M., & Amar, C. B. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2015.06.029 · Cited by 29

Large-scale robust transductive support vector machines

Çevıkalp, H., & Franc, V. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.01.012 · Cited by 31

Discriminative Learning for Automatic Staging of Placental Maturity via Multi-layer Fisher Vector

Lei, B., Yao, Y., Chen, S., Li, S., Li, W., Ni, D., & Wang, T. (2015) · Scientific Reports · doi:10.1038/srep12818 · Cited by 28

Recommendations for recognizing video events by concept vocabularies

Habibian, A., & Snoek, C. G. M. (2014) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2014.02.003 · Cited by 28

Approximate Fisher Kernels of Non-iid Image Models for Image Categorization

Cinbiş, R. G., Verbeek, J. J., & Schmid, C. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2484342 · Cited by 29

Image classification by search with explicitly and implicitly semantic representations

Zhang, C., Zhu, G., Huang, Q., & Tian, Q. (2016) · Information Sciences · doi:10.1016/j.ins.2016.10.019 · Cited by 28

Incremental Codebook Adaptation for Visual Representation and Categorization

Zhang, C., Cheng, J., & Tian, Q. (2017) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2726079 · Cited by 28

ER3: A Unified Framework for Event Retrieval, Recognition and Recounting

Gao, Z., Hua, G., Zhang, D., Jojić, N., Wang, L., Xue, J., & Zheng, N. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.227 · Cited by 28

Image-level classification by hierarchical structure learning with visual and semantic similarities

Zhang, C., Cheng, J., & Tian, Q. (2017) · Information Sciences · doi:10.1016/j.ins.2017.09.024 · Cited by 28

Neighborhood-Correction Algorithm for Classification of Normal and Malignant Cells

Pan, Y., Liu, M., Xia, Y., & Shen, D. G. (2019) · Lecture notes in bioengineering · doi:10.1007/978-981-15-0798-4_8 · Cited by 28

Ship Detection in SAR Images by Aggregating Densities of Fisher Vectors: Extension to a Global Perspective

Wang, X., Li, G., Plaza, A., & He, Y. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3073053 · Cited by 29

Adaptive multi-feature fusion via cross-entropy normalization for effective image retrieval

Ma, W., Zhou, T., Qin, J., Xiang, X., Tan, Y., & Cai, Z. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103119 · Cited by 28

A scalable pattern spotting system for historical documents

En, S., Petitjean, C., Nicolas, S., & Heutte, L. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.01.014 · Cited by 28

Multi-modal learning for affective content analysis in movies

Yi, Y., & Wang, H. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-5662-9 · Cited by 28

Contextual Embeddings-Based Web Page Categorization Using the Fine-Tune BERT Model

Nandanwar, A. K., & Choudhary, J. (2023) · Symmetry · doi:10.3390/sym15020395 · Cited by 30

Interferences in Match Kernels

Murray, N., Jeǵou, H., Perronnin, F., & Zisserman, A. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2615621 · Cited by 28

Image classification towards transmission line fault detection via learning deep quality-aware fine-grained categorization

Wang, Y., Li, Q., & Chen, B. (2019) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2019.102647 · Cited by 27

Real-time hand posture recognition using hand geometric features and Fisher Vector

Fang, L., Liang, N., Kang, W., Wang, Z., & Feng, D. D. (2019) · Signal Processing Image Communication · doi:10.1016/j.image.2019.115729 · Cited by 27

Fake Generated Painting Detection Via Frequency Analysis

Bai, Y. S., Guo, Y., Wei, J., Lu, L., Wang, R., & Wang, Y. (2020) · Proceedings - International Conference on Image Processing · doi:10.1109/icip40778.2020.9190892 · Cited by 27

Deep feature extraction and motion representation for satellite video scene classification

Gu, Y., Liu, H., Wang, T., Li, S., & Gao, G. (2020) · Science China Information Sciences · doi:10.1007/s11432-019-2784-4 · Cited by 27

Wi-HSNN: A subnetwork-based encoding structure for dimension reduction and food classification via harnessing multi-CNN model high-level features

Zhang, W., Wu, Q. M. J., & Yang, Y. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.07.018 · Cited by 27

Human Activity Recognition Algorithm in Video Sequences Based on Integration of Magnitude and Orientation Information of Optical Flow

Kushwaha, A., Khare, A., & Khare, M. (2021) · International Journal of Image and Graphics · doi:10.1142/s0219467822500097 · Cited by 27

Impact evaluation of deep learning on image segmentation for automatic bluefin tuna sizing

Muñoz‐Benavent, P., Martínez-Peiró, J., Andreu-Garcı́a, G., Puig-Pons, V., Espinosa, V., Pérez–Arjona, I., de-la-Gándara, F., & Ortega, A. (2022) · Aquacultural Engineering · doi:10.1016/j.aquaeng.2022.102299 · Cited by 27

A comprehensive evaluation of local detectors and descriptors

Wu, S., Oerlemans, A. A. J., Bakker, E., & Lew, M. (2017) · Signal processing. Image communication · doi:10.1016/j.image.2017.06.010 · Cited by 28

VideoWhisper: Toward Discriminative Unsupervised Video Feature Learning With Attention-Based Recurrent Neural Networks

Zhao, N., Zhang, H., Hong, R., Wang, M., & Chua, T. (2017) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2722687 · Cited by 27

Pointly-Supervised Action Localization

Mettes, P., & Snoek, C. G. M. (2018) · International Journal of Computer Vision · doi:10.1007/s11263-018-1120-4 · Cited by 26

Learning to detect video events from zero or very few video examples

Tzelepis, C., Galanopoulos, D., Mezaris, V., & Patras, I. (2015) · Image and Vision Computing · doi:10.1016/j.imavis.2015.09.005 · Cited by 25

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval

Zhang, Y., Wu, J., & Cai, J. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2549360 · Cited by 26

Food Image Recognition Using Covariance of Convolutional Layer Feature Maps

Tatsuma, A., & Aono, M. (2016) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.2015edl8212 · Cited by 28

3D Human Action Recognition Using a Single Depth Feature and Locality-Constrained Affine Subspace Coding

Liang, C., Qi, L., He, Y., & Guan, L. (2017) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2715045 · Cited by 26

Fisher vector for scene character recognition: A comprehensive evaluation

Shi, C., Wang, Y., Jia, F., He, K., Wang, C., & Xiao, B. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.06.022 · Cited by 26

Gaussian-Induced Convolution for Graphs

Jiang, J., Cui, Z., Xu, C., & Yang, J. J. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33014007 · Cited by 27

Classification of Marine Vessels with Multi-Feature Structure Fusion

Zhang, E., Wang, K., & Lin, G. (2019) · Applied Sciences · doi:10.3390/app9102153 · Cited by 26

LieToMe: An Ensemble Approach for Deception Detection from Facial Cues

Avola, D., Cascio, M., Cinque, L., Fagioli, A., & Foresti, G. L. (2020) · International Journal of Neural Systems · doi:10.1142/s0129065720500689 · Cited by 26

Multimodal Deception Detection Using Automatically Extracted Acoustic, Visual, and Lexical Features

Zhang, J., Levitan, S. I., & Hirschberg, J. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2320 · Cited by 27

Deep Gaussian mixture model based instance relevance estimation for multiple instance learning applications

Waqas, M., Tahir, M. A., & Qureshi, R. (2022) · Applied Intelligence · doi:10.1007/s10489-022-04045-7 · Cited by 26

Unsupervised Multimodal Learning for Dependency-Free Personality Recognition

Ghassemi, S., Zhang, T., van Breda, W., Koutsoumpis, A., Oostrom, J. K., Holtrop, D., & de Vries, R. E. (2023) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2023.3318367 · Cited by 32

Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual Recognition

Sikdar, A., Liu, Y., Kedarisetty, S., Zhao, Y., Ahmed, A. A., & Behera, A. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-024-02260-y · Cited by 27

Cost-Sensitive Two-Stage Depression Prediction Using Dynamic Visual Clues

Ma, X., Huang, D., Wang, Y., & Wang, Y. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-54184-6_21 · Cited by 25

Robust and Efficient Modulation Recognition Based on Local Sequential IQ Features

Xiong, W., Bogdanov, P., & Zheleva, M. Z. (2019) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom.2019.8737397 · Cited by 26

Ensemble Learning Approaches Based on Covariance Pooling of CNN Features for High Resolution Remote Sensing Scene Classification

Akodad, S., Bombrun, L., Xia, J., Berthoumieu, Y., & Germain, C. (2020) · Remote Sensing · doi:10.3390/rs12203292 · Cited by 27

Fast and robust video-based exercise classification via body pose tracking and scalable multivariate time series classifiers

Singh, A., Bevilacqua, A., Nguyen, T. L., Hu, F., McGuinness, K., O’Reilly, M., Whelan, D. F., Caulfield, B., & Ifrim, G. (2022) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-022-00895-4 · Cited by 26

Selective Pooling Vector for Fine-Grained Recognition

Chen, G., Yang, J., Jin, H., Shechtman, E., Brandt, J., & Han, T. X. (2015) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2015.119 · Cited by 25

An integrated artificial vision framework for assisting visually impaired users

Chessa, M., Noceti, N., Odone, F., Solari, F., Sosa-García, J., & Zini, L. (2016) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2015.11.007 · Cited by 25

Frontiers of Multimedia Research

Chang, S.-F. (2017) · doi:10.1145/3122865 · Cited by 26

A Students’ Action Recognition Database In Smart Classroom

Li, X., Wang, M., Zeng, W., & Lu, W. (2019) · International Conference on Computer Science & Education (ICCSE) · doi:10.1109/iccse.2019.8845330 · Cited by 25

3D Point Cloud Descriptors in Hand-crafted and Deep Learning Age: State-of-the-ArtPreprint

Han, X.-F., Sun, S., Song, X., & Xiao, G. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.02297 · Cited by 43

Deep Learning for Scene Classification: A SurveyPreprint

Zeng, D., Liao, M., Tavakolian, M., Guo, Y., Zhou, B., Hu, D., Pietikäinen, M., & Liu, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2101.10531 · Cited by 44

Automatic Recognition of Emotions and Membership in Group Videos

Mou, W., Güneş, H., & Patras, I. (2016) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2016.185 · Cited by 24

An ELM-Embedded Deep Learning Based Intelligent Recognition System for Computer Numeric Control Machine Tools

Luo, L., Yang, Z.-X., Tang, L., & Zhang, K. (2020) · IEEE Access · doi:10.1109/access.2020.2965284 · Cited by 25

FE-Fusion-VPR: Attention-Based Multi-Scale Network Architecture for Visual Place Recognition by Fusing Frames and Events

Hou, K., Kong, D., Jiang, J., Zhuang, H., Huang, X., & Fang, Z. (2023) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2023.3268850 · Cited by 26

Online Domain Adaptation for Multi-Object Tracking

Gaidon, A., & Vig, E. (2015) · British Machine Vision Conference (BMVC) · doi:10.5244/c.29.3 · Cited by 25

Aggregating Image and Text Quantized Correlated Components

Tran, T. Q. N., Borgne, H. L., & Crucianu, M. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.225 · Cited by 24

Multi-label image classification with recurrently learning semantic dependencies

Chen, L. F., Wang, R., Yang, J., Xue, L., & Hu, M. Q. (2018) · The Visual Computer · doi:10.1007/s00371-018-01615-0 · Cited by 24

Research on key technologies of intelligent transportation based on image recognition and anti-fatigue driving

Wang, J., Yu, X., Liu, Q., & Yang, Z. (2019) · EURASIP Journal on Image and Video Processing · doi:10.1186/s13640-018-0403-6 · Cited by 24

Crowd Video Event Classification using Convolutional Neural Network

Shri, S. J., & Jothilakshmi, S. (2019) · Computer Communications · doi:10.1016/j.comcom.2019.07.027 · Cited by 24

Author manuscript, published in "International Journal of Computer Vision (2013)" International Journal of Computer Vision manuscript No. (will be inserted by the editor) Image Classification with the Fisher Vector: Theory and Practice

Sánchez, J., Perronnin, F., Mensink, T., & Verbeek, J. J. (2013)

International Journal of Computer Vision manuscript No. (will be inserted by the editor) Image Classification with the Fisher Vector: Theory and Practice

Sánchez, J., Perronnin, F., Mensink, T., & Verbeek, J. J. (2014)

and Practice

Sánchez, J., Perronnin, F., Mensink, T., Verbeek, J. J., Sánchez, J., & Perronnin, F. (2014)

Local Patch Vectors Encoded by Fisher Vectors for Image Classification

Chen, S., Liu, H., Zeng, X., Qian, S., Wei, W., Wu, G., & Duan, B. (2018) · Information · doi:10.3390/info9020038 · Cited by 7

Fisher Vectors: Beyond Bag-of-Visual-Words Image Representations

Csurka, G., & Perronnin, F. (2011) · Communications in computer and information science · doi:10.1007/978-3-642-25382-9_2 · Cited by 65