Chen, J.Z.[Jing-Zhou],
Wang, S.H.[Shi-Hao],
Chen, L.[Ling],
Cai, H.B.[Hai-Bin],
Qian, Y.T.[Yun-Tao],
Incremental Detection of Remote Sensing Objects With Feature Pyramid
and Knowledge Distillation,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI
2112
Feature extraction, Remote sensing, Training, Object detection,
Adaptation models, Proposals, Detectors, Deep learning, remote sensing
BibRef
Yang, D.B.[Dong-Bao],
Zhou, Y.[Yu],
Zhang, A.[Aoting],
Sun, X.R.[Xu-Rui],
Wu, D.[Dayan],
Wang, W.P.[Wei-Ping],
Ye, Q.X.[Qi-Xiang],
Multi-View correlation distillation for incremental object detection,
PR(131), 2022, pp. 108863.
Elsevier DOI
2208
Object detection, Incremental learning,
Catastrophic forgetting, Knowledge distillation
BibRef
Wang, G.H.[Guo-Hua],
Ge, Y.F.[Yi-Fan],
Wu, J.X.[Jian-Xin],
Distilling Knowledge by Mimicking Features,
PAMI(44), No. 11, November 2022, pp. 8183-8195.
IEEE DOI
2210
Hash functions, Training, Standards, Residual neural networks,
Radio frequency, Numerical models, Convolutional neural networks,
object detection
BibRef
He, Y.Y.[Yin-Yin],
Wu, J.X.[Jian-Xin],
Wei, X.S.[Xiu-Shen],
Distilling Virtual Examples for Long-tailed Recognition,
ICCV21(235-244)
IEEE DOI
2203
Visualization, Predictive models, Benchmark testing,
Recognition and classification,
BibRef
Zhang, L.[Li],
Wu, X.Q.[Xiang-Qian],
Latent Space Semantic Supervision Based on Knowledge Distillation for
Cross-Modal Retrieval,
IP(31), 2022, pp. 7154-7164.
IEEE DOI
2212
Feature extraction, Semantics, Object detection, Correlation,
Context modeling, Recurrent neural networks, Multitasking,
knowledge distillation
BibRef
Tang, R.N.[Rui-Ning],
Liu, Z.Y.[Zhen-Yu],
Li, Y.G.[Yang-Guang],
Song, Y.[Yiguo],
Liu, H.[Hui],
Wang, Q.[Qide],
Shao, J.[Jing],
Duan, G.F.[Gui-Fang],
Tan, J.R.[Jiang-Rong],
Task-balanced distillation for object detection,
PR(137), 2023, pp. 109320.
Elsevier DOI
2302
Object detection, Knowledge distillation
BibRef
Liu, Y.F.[Yi-Fan],
Shu, C.Y.[Chang-Yong],
Wang, J.D.[Jing-Dong],
Shen, C.H.[Chun-Hua],
Structured Knowledge Distillation for Dense Prediction,
PAMI(45), No. 6, June 2023, pp. 7035-7049.
IEEE DOI
2305
Task analysis, Semantics, Training, Object detection,
Image segmentation, Estimation, Knowledge engineering, dense prediction
BibRef
Zhou, W.[Wujie],
Sun, F.[Fan],
Jiang, Q.P.[Qiu-Ping],
Cong, R.[Runmin],
Hwang, J.N.[Jenq-Neng],
WaveNet: Wavelet Network With Knowledge Distillation for RGB-T
Salient Object Detection,
IP(32), 2023, pp. 3027-3039.
IEEE DOI
2306
Transformers, Feature extraction, Discrete wavelet transforms,
Training, Knowledge engineering, Cross layer design, edge-aware module
BibRef
Li, Z.H.[Zhi-Hui],
Xu, P.F.[Peng-Fei],
Chang, X.J.[Xiao-Jun],
Yang, L.[Luyao],
Zhang, Y.Y.[Yuan-Yuan],
Yao, L.[Lina],
Chen, X.J.[Xiao-Jiang],
When Object Detection Meets Knowledge Distillation: A Survey,
PAMI(45), No. 8, August 2023, pp. 10555-10579.
IEEE DOI
2307
Survey, Knowledge Distillation. Task analysis, Computational modeling, Analytical models,
Image coding, Solid modeling, Object detection,
weakly supervised object detection
BibRef
Yang, A.[Aijia],
Lin, S.[Sihao],
Yeh, C.H.[Chung-Hsing],
Shu, M.[Minglei],
Yang, Y.[Yi],
Chang, X.J.[Xiao-Jun],
Context Matters:
Distilling Knowledge Graph for Enhanced Object Detection,
MultMed(26), 2024, pp. 487-500.
IEEE DOI
2402
Detectors, Knowledge graphs, Semantics, Object detection,
Transformers, Visualization, Image edge detection,
knowledge graph
BibRef
Pei, S.[Shaotong],
Zhang, H.[Hangyuan],
Zhu, Y.X.[Yu-Xin],
Hu, C.[Chenlong],
Lightweight transmission line defect identification method based on
OFN network and distillation method,
IET-IPR(18), No. 12, 2024, pp. 3518-3529.
DOI Link
2411
convolutional neural nets, image recognition, insulators, object detection
BibRef
Lan, Q.Z.[Qi-Zhen],
Tian, Q.[Qing],
Gradient-Guided Knowledge Distillation for Object Detectors,
WACV24(423-432)
IEEE DOI Code:
WWW Link.
2404
Deep learning, Codes, Computational modeling, Object detection,
Detectors, Feature extraction, Algorithms
BibRef
Yang, L.[Longrong],
Zhou, X.[Xianpan],
Li, X.[Xuewei],
Qiao, L.[Liang],
Li, Z.[Zheyang],
Yang, Z.W.[Zi-Wei],
Wang, G.[Gaoang],
Li, X.[Xi],
Bridging Cross-task Protocol Inconsistency for Distillation in Dense
Object Detection,
ICCV23(17129-17138)
IEEE DOI Code:
WWW Link.
2401
BibRef
Lao, S.S.[Shan-Shan],
Song, G.L.[Guang-Lu],
Liu, B.X.[Bo-Xiao],
Liu, Y.[Yu],
Yang, Y.J.[Yu-Jiu],
UniKD: Universal Knowledge Distillation for Mimicking Homogeneous or
Heterogeneous Object Detectors,
ICCV23(6339-6349)
IEEE DOI
2401
BibRef
Du, X.[Xuanyi],
Wan, W.T.[Wei-Tao],
Sun, C.[Chong],
Li, C.[Chen],
Weak-shot Object Detection through Mutual Knowledge Transfer,
CVPR23(19671-19680)
IEEE DOI
2309
BibRef
Tang, S.[Sanli],
Zhang, Z.Y.[Zhong-Yu],
Cheng, Z.Z.[Zhan-Zhan],
Lu, J.[Jing],
Xu, Y.L.[Yun-Lu],
Niu, Y.[Yi],
He, F.[Fan],
Distilling Object Detectors with Global Knowledge,
ECCV22(IX:422-438).
Springer DOI
2211
BibRef
Liu, L.Z.[Lyu-Zhuang],
Hirakawa, T.[Tsubasa],
Yamashita, T.[Takayoshi],
Fujiyoshi, H.[Hironobu],
Class-Wise FM-NMS for Knowledge Distillation of Object Detection,
ICIP22(1641-1645)
IEEE DOI
2211
Computational modeling, Object detection, Feature extraction,
Computational efficiency, Object detection,
Feature map non-maximum suppression
BibRef
Pei, W.J.[Wen-Jie],
Wu, S.[Shuang],
Mei, D.[Dianwen],
Chen, F.L.[Fang-Lin],
Tian, J.[Jiandong],
Lu, G.M.[Guang-Ming],
Few-Shot Object Detection by Knowledge Distillation Using
Bag-of-Visual-Words Representations,
ECCV22(X:283-299).
Springer DOI
2211
BibRef
Zhao, B.[Borui],
Cui, Q.[Quan],
Song, R.J.[Ren-Jie],
Qiu, Y.[Yiyu],
Liang, J.J.[Jia-Jun],
Decoupled Knowledge Distillation,
CVPR22(11943-11952)
IEEE DOI
2210
Training, Deep learning, Codes, Object detection,
Computer architecture, Feature extraction,
retrieval
BibRef
Yang, Z.D.[Zhen-Dong],
Li, Z.[Zhe],
Jiang, X.H.[Xiao-Hu],
Gong, Y.[Yuan],
Yuan, Z.H.[Ze-Huan],
Zhao, D.[Danpei],
Yuan, C.[Chun],
Focal and Global Knowledge Distillation for Detectors,
CVPR22(4633-4642)
IEEE DOI
2210
Codes, Detectors, Object detection, Feature extraction,
Image classification, Efficient learning and inferences
BibRef
Mal, Z.Y.[Zong-Yang],
Luo, G.[Guan],
Gao, J.[Jin],
Li, L.[Liang],
Chen, Y.X.[Yu-Xin],
Wang, S.[Shaoru],
Zhang, C.X.[Cong-Xuan],
Hu, W.M.[Wei-Ming],
Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language
Knowledge Distillation,
CVPR22(14054-14063)
IEEE DOI
2210
Training, Degradation, Vocabulary, Visualization, Semantics, Detectors,
Object detection, Recognition: detection, categorization,
Vision + language
BibRef
Yao, L.W.[Le-Wei],
Pi, R.J.[Ren-Jie],
Xu, H.[Hang],
Zhang, W.[Wei],
Li, Z.G.[Zhen-Guo],
Zhang, T.[Tong],
G-DetKD: Towards General Distillation Framework for Object Detectors
via Contrastive and Semantic-Guided Feature Imitation,
ICCV21(3571-3580)
IEEE DOI
2203
Semantics, Pipelines, Detectors, Object detection, Benchmark testing,
Feature extraction, Detection and localization in 2D and 3D,
BibRef
Chen, Y.X.[Yi-Xin],
Chen, P.G.[Peng-Guang],
Liu, S.[Shu],
Wang, L.W.[Li-Wei],
Jia, J.Y.[Jia-Ya],
Deep Structured Instance Graph for Distilling Object Detectors,
ICCV21(4339-4348)
IEEE DOI
2203
Codes, Image edge detection, Semantics, Detectors, Object detection,
Knowledge representation,
Detection and localization in 2D and 3D
BibRef
Kim, Y.[Youmin],
Park, J.[Jinbae],
Jang, Y.[YounHo],
Ali, M.[Muhammad],
Oh, T.H.[Tae-Hyun],
Bae, S.H.[Sung-Ho],
Distilling Global and Local Logits with Densely Connected Relations,
ICCV21(6270-6280)
IEEE DOI
2203
Image segmentation, Image recognition, Computational modeling,
Semantics, Object detection, Task analysis,
BibRef
Kim, K.[Kyungyul],
Ji, B.[ByeongMoon],
Yoon, D.[Doyoung],
Hwang, S.[Sangheum],
Self-Knowledge Distillation with Progressive Refinement of Targets,
ICCV21(6547-6556)
IEEE DOI
2203
Training, Knowledge engineering, Adaptation models,
Supervised learning, Neural networks, Object detection,
Recognition and classification
BibRef
Kobayashi, T.[Takumi],
Extractive Knowledge Distillation,
WACV22(1350-1359)
IEEE DOI
2202
Temperature distribution, Analytical models,
Annotations, Transfer learning, Feature extraction, Task analysis,
Deep Learning Object Detection/Recognition/Categorization
BibRef
Nguyen, C.H.[Chuong H.],
Nguyen, T.C.[Thuy C.],
Tang, T.N.[Tuan N.],
Phan, N.L.H.[Nam L. H.],
Improving Object Detection by Label Assignment Distillation,
WACV22(1322-1331)
IEEE DOI
2202
Training, Schedules, Costs, Force, Object detection, Detectors,
Switches, Object Detection/Recognition/Categorization
BibRef
Banitalebi-Dehkordi, A.[Amin],
Knowledge Distillation for Low-Power Object Detection: A Simple
Technique and Its Extensions for Training Compact Models Using
Unlabeled Data,
LPCV21(769-778)
IEEE DOI
2112
Training, Adaptation models,
Computational modeling, Object detection, Computer architecture
BibRef
Chen, P.G.[Peng-Guang],
Liu, S.[Shu],
Zhao, H.S.[Heng-Shuang],
Jia, J.Y.[Jia-Ya],
Distilling Knowledge via Knowledge Review,
CVPR21(5006-5015)
IEEE DOI
2111
Knowledge engineering, Object detection, Task analysis
BibRef
Ji, M.[Mingi],
Shin, S.J.[Seung-Jae],
Hwang, S.H.[Seung-Hyun],
Park, G.[Gibeom],
Moon, I.C.[Il-Chul],
Refine Myself by Teaching Myself: Feature Refinement via
Self-Knowledge Distillation,
CVPR21(10659-10668)
IEEE DOI
2111
Knowledge engineering, Training, Codes, Semantics,
Neural networks, Object detection
BibRef
Okuno, T.[Tomoyuki],
Nakata, Y.[Yohei],
Ishii, Y.[Yasunori],
Tsukizawa, S.[Sotaro],
Lossless AI: Toward Guaranteeing Consistency between Inferences
Before and After Quantization via Knowledge Distillation,
MVA21(1-5)
DOI Link
2109
Training, Quality assurance, Quantization (signal),
Object detection, Network architecture, Real-time systems
BibRef
Chawla, A.[Akshay],
Yin, H.X.[Hong-Xu],
Molchanov, P.[Pavlo],
Alvarez, J.[Jose],
Data-free Knowledge Distillation for Object Detection,
WACV21(3288-3297)
IEEE DOI
2106
Knowledge engineering, Training, Image synthesis,
Neural networks, Object detection
BibRef
Finogeev, E.,
Gorbatsevich, V.,
Moiseenko, A.,
Vizilter, Y.,
Vygolov, O.,
Knowledge Distillation Using GANs for Fast Object Detection,
ISPRS20(B2:583-588).
DOI Link
2012
BibRef
Itsumi, H.,
Beye, F.,
Shinohara, Y.,
Iwai, T.,
Training With Cache:
Specializing Object Detectors From Live Streams Without Overfitting,
ICIP20(1976-1980)
IEEE DOI
2011
Training, Data models, Solid modeling, Adaptation models,
Training data, Streaming media, Legged locomotion, Online training,
Knowledge distillation
BibRef
Farhadi, M.[Mohammad],
Yang, Y.Z.[Ye-Zhou],
TKD: Temporal Knowledge Distillation for Active Perception,
WACV20(942-951)
IEEE DOI
2006
Code, Object Detection.
WWW Link. Temporal knowledge over NN applied over multiple frames.
Adaptation models, Object detection, Visualization,
Computational modeling, Task analysis, Training, Feature extraction
BibRef
Yoshioka, K.,
Lee, E.,
Wong, S.,
Horowitz, M.,
Dataset Culling: Towards Efficient Training of Distillation-Based
Domain Specific Models,
ICIP19(3237-3241)
IEEE DOI
1910
Object Detection, Training Efficiency, Distillation,
Dataset Culling, Deep Learning
BibRef
Kundu, J.N.,
Lakkakula, N.,
Radhakrishnan, V.B.,
UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial
Cross-Task Distillation,
ICCV19(1436-1445)
IEEE DOI
2004
generalisation (artificial intelligence), image classification,
object detection, unsupervised learning, task-transferability,
Adaptation models
BibRef
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Student-Teacher, Teacher-Student, Knowledge Distillation .