13.6.11.1.1 Part Based Fine-Grained Classification

Deng, J.[Jia], Krause, J.[Jonathan], Stark, M., Fei-Fei, L.[Li],
Leveraging the Wisdom of the Crowd for Fine-Grained Recognition,
PAMI(38), No. 4, April 2016, pp. 666-676.
IEEE DOI 1603
BibRef
Earlier: A2, A3, A1, A4:
3D Object Representations for Fine-Grained Categorization,
3DRR13(554-561)
IEEE DOI 1403
BibRef
And: A1, A2, A4, Only:
Fine-Grained Crowdsourcing for Fine-Grained Recognition,
CVPR13(580-587)
IEEE DOI 1309
differences between classes very local. Human in loop. computational geometry. Birds
See also Stanford Cars Dataset. BibRef

Stark, M.[Michael], Krause, J.[Jonathan], Pepik, B.[Bojan], Meger, D.[David], Little, J.J.[James J.], Schiele, B.[Bernt], Koller, D.[Daphne],
Fine-Grained Categorization for 3D Scene Understanding,
BMVC12(36).
DOI Link 1301
BibRef

Krause, J.[Jonathan], Gebru, T.[Timnit], Deng, J.[Jia], Li, L.J.[Li-Jia], Fei-Fei, L.[Li],
Learning Features and Parts for Fine-Grained Recognition,
ICPR14(26-33)
IEEE DOI 1412
Detectors BibRef

Branson, S.[Steve], van Horn, G.[Grant], Wah, C.[Catherine], Perona, P.[Pietro], Belongie, S.J.[Serge J.],
The Ignorant Led by the Blind: A Hybrid Human-Machine Vision System for Fine-Grained Categorization,
IJCV(108), No. 1-2, May 2014, pp. 3-29.
Springer DOI 1405
BibRef

Wah, C.[Catherine], Maji, S.[Subhransu], Belongie, S.J.[Serge J.],
Learning Localized Perceptual Similarity Metrics for Interactive Categorization,
WACV15(502-509)
IEEE DOI 1503
BibRef

Wah, C.[Catherine], van Horn, G.[Grant], Branson, S.[Steve], Maji, S.[Subhransu], Perona, P.[Pietro], Belongie, S.J.[Serge J.],
Similarity Comparisons for Interactive Fine-Grained Categorization,
CVPR14(859-866)
IEEE DOI 1409
BibRef

Branson, S.[Steve], Perona, P.[Pietro], Belongie, S.J.[Serge J.],
Strong supervision from weak annotation: Interactive training of deformable part models,
ICCV11(1832-1839).
IEEE DOI 1201
Large scale learning of structured models. Interactive (semi-automated) labeling and learning. BibRef

Zhang, Y.[Yu], Wei, X.S.[Xiu-Shen], Wu, J.X.[Jian-Xin], Cai, J.F.[Jian-Fei], Lu, J.B.[Jiang-Bo], Nguyen, V.A.[Viet-Anh], Do, M.N.[Minh N.],
Weakly Supervised Fine-Grained Categorization With Part-Based Image Representation,
IP(25), No. 4, April 2016, pp. 1713-1725.
IEEE DOI 1604
Birds BibRef

Nakayama, H.[Hideki], Tsuda, T.[Tomoya],
Efficient Two-Step Middle-Level Part Feature Extraction for Fine-Grained Visual Categorization,
IEICE(E99-D), No. 6, June 2016, pp. 1626-1634.
WWW Link. 1606
BibRef

Huang, C., He, Z., Cao, G., Cao, W.,
Task-Driven Progressive Part Localization for Fine-Grained Object Recognition,
MultMed(18), No. 12, December 2016, pp. 2372-2383.
IEEE DOI 1612
BibRef
Earlier: A1, A2, Only:
Task-driven progressive part localization for fine-grained recognition,
WACV16(1-9)
IEEE DOI 1606
Correlation BibRef

Yao, H.T.[Han-Tao], Zhang, D.M.[Dong-Ming], Li, J.T.[Jin-Tao], Zhou, J.S.[Jian-She], Zhang, S.L.[Shi-Liang], Zhang, Y.D.[Yong-Dong],
DSP: Discriminative Spatial Part modeling for Fine-Grained Visual Categorization,
IVC(63), No. 1, 2017, pp. 24-37.
Elsevier DOI 1706
Orientational, Spatial, Part model BibRef

Xie, G.S.[Guo-Sen], Zhang, X.Y.[Xu-Yao], Yang, W.H.[Wen-Han], Xu, M.L.[Ming-Liang], Yan, S.C.[Shui-Cheng], Liu, C.L.[Cheng-Lin],
LG-CNN: From local parts to global discrimination for fine-grained recognition,
PR(71), No. 1, 2017, pp. 118-131.
Elsevier DOI 1707
Fine-grained, recognition BibRef

Sun, T.[Ting], Sun, L.[Lin], Yeung, D.Y.[Dit-Yan],
Fine-grained categorization via CNN-based automatic extraction and integration of object-level and part-level features,
IVC(64), No. 1, 2017, pp. 47-66.
Elsevier DOI 1708
Fine-grained categorization BibRef

Zheng, H., Fu, J., Zha, Z., Luo, J., Mei, T.,
Learning Rich Part Hierarchies With Progressive Attention Networks for Fine-Grained Image Recognition,
IP(29), No. 1, 2020, pp. 476-488.
IEEE DOI 1910
convolutional neural nets, image recognition, learning (artificial intelligence), optimisation, progressive attention BibRef

Zhang, Y.B.[Ya-Bin], Jia, K.[Kui], Wang, Z.X.[Zhi-Xin],
Part-Aware Fine-Grained Object Categorization Using Weakly Supervised Part Detection Network,
MultMed(22), No. 5, May 2020, pp. 1345-1357.
IEEE DOI 2005
Proposals, Detectors, Task analysis, Streaming media, Feature extraction, Benchmark testing, Supervised learning, weakly supervised learning BibRef

Liu, X., Han, Z., Liu, Y.S., Zwicker, M.,
Fine-Grained 3D Shape Classification With Hierarchical Part-View Attention,
IP(30), 2021, pp. 1744-1758.
IEEE DOI 2101
Shape, Semantics, Feature extraction, Proposals, Automobiles, Airplanes, recurrent neural network BibRef

Zheng, X.T.[Xiang-Tao], Qi, L.[Lei], Ren, Y.T.[Yu-Tao], Lu, X.Q.[Xiao-Qiang],
Fine-Grained Visual Categorization by Localizing Object Parts With Single Image,
MultMed(23), 2021, pp. 1187-1199.
IEEE DOI 2105
Feature extraction, Detectors, Training, Image representation, Visualization, Semantics, Birds, Dropout learning BibRef

Zhao, Y.F.[Yi-Fan], Li, J.[Jia], Chen, X.[Xiaowu], Tian, Y.H.[Yong-Hong],
Part-Guided Relational Transformers for Fine-Grained Visual Recognition,
IP(30), 2021, pp. 9470-9481.
IEEE DOI 2112
Transformers, Visualization, Correlation, Task analysis, Feature extraction, Semantics, Costs, relationship BibRef

Han, J.W.[Jun-Wei], Yao, X.[Xiwen], Cheng, G.[Gong], Feng, X.X.[Xiao-Xu], Xu, D.[Dong],
P-CNN: Part-Based Convolutional Neural Networks for Fine-Grained Visual Categorization,
PAMI(44), No. 2, February 2022, pp. 579-590.
IEEE DOI 2201
Visualization, Training, Detectors, Streaming media, Measurement, Feature extraction, Convolutional neural networks, fine-grained visual categorization BibRef

Liu, M.[Man], Zhang, C.J.[Chun-Jie], Bai, H.[Huihui], Zhang, R.[Riquan], Zhao, Y.[Yao],
Cross-Part Learning for Fine-Grained Image Classification,
IP(31), 2022, pp. 748-758.
IEEE DOI 2201
Transformers, Location awareness, Task analysis, Proposals, Feature extraction, Navigation, transformer BibRef

Yu, X.H.[Xiao-Han], Zhao, Y.[Yang], Gao, Y.S.[Yong-Sheng],
SPARE: Self-supervised part erasing for ultra-fine-grained visual categorization,
PR(128), 2022, pp. 108691.
Elsevier DOI 2205
Self-Supervised part erasing, Ultra-fine-grained visual categorization, Weakly-supervised part segmentation BibRef

Liu, H.B.[Hua-Bin], Li, J.G.[Jian-Guo], Li, D.[Dian], See, J.[John], Lin, W.Y.[Wei-Yao],
Learning Scale-Consistent Attention Part Network for Fine-Grained Image Recognition,
MultMed(24), 2022, pp. 2902-2913.
IEEE DOI 2206
Image recognition, Task analysis, Logic gates, Location awareness, Visualization, Training, Object detection, attention part BibRef

Wang, S.J.[Shi-Jie], Wang, Z.H.[Zhi-Hui], Li, H.J.[Hao-Jie], Chang, J.L.[Jian-Long], Ouyang, W.L.[Wan-Li], Tian, Q.[Qi],
Semantic-Guided Information Alignment Network for Fine-Grained Image Recognition,
CirSysVideo(33), No. 11, November 2023, pp. 6558-6570.
IEEE DOI 2311
BibRef

Yan, T.T.[Tian-Tian], Li, H.J.[Hao-Jie], Sun, B.[Baoli], Wang, Z.H.[Zhi-Hui], Luo, Z.X.[Zhong-Xuan],
Discriminative Feature Mining and Enhancement Network for Low-Resolution Fine-Grained Image Recognition,
CirSysVideo(32), No. 8, August 2022, pp. 5319-5330.
IEEE DOI 2208
Feature extraction, Image recognition, Task analysis, Reliability, Image reconstruction, Automobiles, Training, part selection BibRef

Han, X.[Xuan], You, M.Y.[Ming-Yu], Lu, P.[Ping],
Improving the Conditional Fine-Grained Image Generation With Part Perception,
MultMed(26), 2024, pp. 4792-4804.
IEEE DOI 2403
Image synthesis, Task analysis, Semantics, Generators, Training, Benchmark testing, Indexes, Fine-grained image generation, part perception BibRef

Wang, C.M.[Chuan-Ming], Fu, H.Y.[Hui-Yuan], Ma, H.D.[Hua-Dong],
Learning Mutually Exclusive Part Representations for Fine-Grained Image Classification,
MultMed(26), 2024, pp. 3113-3124.
IEEE DOI 2402
Feature extraction, Image classification, Filter banks, Annotations, Training, Semantics, Task analysis, multi-granularity BibRef

Wang, C.M.[Chuan-Ming], Fu, H.Y.[Hui-Yuan], Liu, P.[Peiye], Ma, H.D.[Hua-Dong],
Part-Level Relationship Learning for Fine-Grained Few-Shot Image Classification,
MultMed(27), 2025, pp. 1448-1460.
IEEE DOI 2503
Measurement, Feature extraction, Image classification, Extraterrestrial measurements, Few shot learning, Prototypes, relationship learning BibRef

Wang, J.H.[Jia-Hui], Xu, Q.[Qin], Jiang, B.[Bo], Luo, B.[Bin], Tang, J.H.[Jin-Hui],
Multi-Granularity Part Sampling Attention for Fine-Grained Visual Classification,
IP(33), 2024, pp. 4529-4542.
IEEE DOI Code:
WWW Link. 2408
Feature extraction, Semantics, Visualization, Shape, Location awareness, Attention mechanisms, Transformers, attention mechanism BibRef

Korsch, D.[Dimitri], Shadaydeh, M.[Maha], Denzler, J.[Joachim],
Simplified Concrete Dropout - Improving the Generation of Attribution Masks for Fine-grained Classification,
IJCV(133), No. 8, August 2025, pp. 5857-5871.
Springer DOI 2508
BibRef

Korsch, D.[Dimitri], Bodesheim, P.[Paul], Denzler, J.[Joachim],
Classification-Specific Parts for Improving Fine-Grained Visual Categorization,
GCPR19(62-75).
Springer DOI 1911
BibRef

Xie, X.X.[Xing-Xing], Cheng, G.[Gong], Li, W.B.[Wen-Bo], Lang, C.[Chunbo], Zhang, P.[Peng], Yao, Y.Q.[Yan-Qing], Han, J.W.[Jun-Wei],
Learning Discriminative Representation for Fine-Grained Object Detection in Remote Sensing Images,
CirSysVideo(35), No. 8, August 2025, pp. 8197-8208.
IEEE DOI Code:
WWW Link. 2508
Object detection, Remote sensing, Feature extraction, Airplanes, Training, Detectors, Accuracy, Location awareness, confusion-minimized loss BibRef

Yang, Y.Q.[Yu-Qi], Chang, D.L.[Dong-Liang], Du, R.[Ruoyi], Song, Y.Z.[Yi-Zhe], Ma, Z.Y.[Zhan-Yu],
Adaptive Multi-Resolution Feature Fusion for Fine-Grained Visual Classification,
CirSysVideo(35), No. 8, August 2025, pp. 8252-8264.
IEEE DOI Code:
WWW Link. 2508
Image resolution, Feature extraction, Training, Accuracy, Visualization, Image recognition, Adaptation models, meta-learning BibRef

Saha, O.[Oindrila], Maji, S.[Subhransu],
PARTICLE: Part Discovery and Contrastive Learning for Fine-grained Recognition,
VIPriors23(167-176)
IEEE DOI 2401
BibRef

Zhang, L.B.[Lian-Bo], Huang, S.L.[Shao-Li], Liu, W.[Wei],
Intra-class Part Swapping for Fine-Grained Image Classification,
WACV21(3208-3217)
IEEE DOI 2106
Location awareness, Training, Image recognition, Training data, Data models, Noise measurement BibRef

Wang, X.G.[Xiao-Gang], Sun, X.[Xun], Cao, X.Y.[Xin-Yu], Xu, K.[Kai], Zhou, B.[Bin],
Learning Fine-Grained Segmentation of 3D Shapes without Part Labels,
CVPR21(10271-10280)
IEEE DOI 2111
Training, Solid modeling, Shape, Semantics, Graph neural networks BibRef

Yu, F.G.[Feng-Gen], Liu, K.[Kun], Zhang, Y.[Yan], Zhu, C.Y.[Chen-Yang], Xu, K.[Kai],
PartNet: A Recursive Part Decomposition Network for Fine-Grained and Hierarchical Shape Segmentation,
CVPR19(9483-9492).
IEEE DOI 2002
BibRef

Ge, W.F.[Wei-Feng], Lin, X.R.[Xiang-Ru], Yu, Y.[Yizhou],
Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification From the Bottom Up,
CVPR19(3029-3038).
IEEE DOI 2002
BibRef

Mo, K.[Kaichun], Zhu, S.L.[Shi-Lin], Chang, A.X.[Angel X.], Yi, L.[Li], Tripathi, S.[Subarna], Guibas, L.J.[Leonidas J.], Su, H.[Hao],
PartNet: A Large-Scale Benchmark for Fine-Grained and Hierarchical Part-Level 3D Object Understanding,
CVPR19(909-918).
IEEE DOI 2002
BibRef

Xin, Q., Lv, T., Gao, H.,
Random Part Localization Model for Fine Grained Image Classification,
ICIP19(420-424)
IEEE DOI 1910
fine-grained, convolutional neural network, random part localization BibRef

Dai, X., Southall, B., Trinh, N., Matei, B.,
Efficient Fine-Grained Classification and Part Localization Using One Compact Network,
CEFR-LCV17(996-1004)
IEEE DOI 1802
Automobiles, Birds, Convolution, Switches, Training BibRef

Lam, M., Mahasseni, B., Todorovic, S.,
Fine-Grained Recognition as HSnet Search for Informative Image Parts,
CVPR17(6497-6506)
IEEE DOI 1711
Feature extraction, Image recognition, Object recognition, Proposals, Search problems, Trajectory BibRef

Zhang, J.Y.[Jia-Yi], Xu, S.P.[Shi-Pu], Liu, Y.[Yang], Hao, Y.P.[Yong-Ping],
Research on the identification method of micro assembly part,
ICIVC17(295-298)
IEEE DOI 1708
Charge coupled devices, Control systems, Image edge detection, Noise reduction, Shape, Smoothing methods, Visualization, image recognition, micro assembly, template matching BibRef

Takahashi, T.[Toru], Kudo, Y.[Yuta], Ishiyama, R.[Rui],
Mass-produced parts traceability system based on automated scanning of 'Fingerprint of Things',
MVA17(202-206)
DOI Link 1708
Fasteners, Fingerprint recognition, Image matching, Imaging, Metals, Mobile handsets, Prototypes. Too small for id tags. BibRef

Zhang, H.[Han], Xu, T.[Tao], Elhoseiny, M.[Mohamed], Huang, X.L.[Xiao-Lei], Zhang, S.T.[Shao-Ting], Elgammal, A.E.[Ahmed E.], Metaxas, D.N.[Dimitris N.],
SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-Grained Recognition,
CVPR16(1143-1152)
IEEE DOI 1612
BibRef

Shih, K.J.[Kevin J.], Mallya, A.[Arun], Singh, S.[Saurabh], Hoiem, D.[Derek],
Part Localization using Multi-Proposal Consensus for Fine-Grained Categorization,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Li, D.[Dong], Li, Y.[Yali], Wang, S.J.[Sheng-Jin],
Selective parts for fine-grained recognition,
ICIP15(922-926)
IEEE DOI 1512
Fine-grained recognition BibRef

Liao, L.[Liang], Hu, R.M.[Rui-Min], Xiao, J.[Jun], Wang, Q.[Qi], Xiao, J.[Jing], Chen, J.[Jun],
Exploiting effects of parts in fine-grained categorization of vehicles,
ICIP15(745-749)
IEEE DOI 1512
DPM; SVM; fine-grained categorization; vehicle parts BibRef

Lin, D.[Di], Shen, X.Y.[Xiao-Yong], Lu, C.[Cewu], Jia, J.Y.[Jia-Ya],
Deep LAC: Deep localization, alignment and classification for fine-grained recognition,
CVPR15(1666-1674)
IEEE DOI 1510
part localization, alignment, and classification in one deep neural network. BibRef

Krause, J.[Jonathan], Jin, H.L.[Hai-Lin], Yang, J.C.[Jian-Chao], Fei-Fei, L.[Li],
Fine-grained recognition without part annotations,
CVPR15(5546-5555)
IEEE DOI 1510
BibRef

Zhang, N.[Ning], Donahue, J.[Jeff], Girshick, R.[Ross], Darrell, T.J.[Trevor J.],
Part-Based R-CNNs for Fine-Grained Category Detection,
ECCV14(I: 834-849).
Springer DOI 1408
BibRef

Xie, L.X.[Ling-Xi], Tian, Q.[Qi], Hong, R.C.[Ri-Chang], Yan, S.C.[Shui-Cheng], Zhang, B.[Bo],
Hierarchical Part Matching for Fine-Grained Visual Categorization,
ICCV13(1641-1648)
IEEE DOI 1403
Fine-Grained Visual Categorization BibRef

Zhang, N.[Ning], Farrell, R.[Ryan], Iandola, F.[Forrest], Darrell, T.J.[Trevor J.],
Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction,
ICCV13(729-736)
IEEE DOI 1403
BibRef

Chai, Y.N.[Yu-Ning], Lempitsky, V.[Victor], Zisserman, A.[Andrew],
Symbiotic Segmentation and Part Localization for Fine-Grained Categorization,
ICCV13(321-328)
IEEE DOI 1403
Detection; Fine-Grained; Object Recognition; Segmentation BibRef

Zheng, Y.B.[Ying-Bin], Jiang, Y.G.[Yu-Gang], Xue, X.Y.[Xiang-Yang],
Learning Hybrid Part Filters for Scene Recognition,
ECCV12(V: 172-185).
Springer DOI 1210
Not the whole object, but parts that may be shared with multiple objects. BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Fine-Grained Classification Using CNN, Convolutional Neural Networks .