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ORCIDJie Lin 0001
Person information
- affiliation: Institute for Infocomm Research, Singapore
- affiliation (former): Beijing Jiaotong University, School of Computer Science and Technology, Beijing, China
- affiliation (former): Peking University, Institute of Digital Media, Beijing, China
Other persons with the same name
- Jie Lin — disambiguation page
- Jie Lin 0002
![[0000-0003-3476-110X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-3476-110X")
— Xian Jiaotong University, School of Electronic and Information Engineering, China - Jie Lin 0003 (aka: Jane Lin 0001) — University of Illinois at Chicago, Department of Civil and Materials Engineering, USA
- Jie Lin 0004 — AMD Inc., Sunnyvale, CA, USA (and 1 more)
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2020 – today
- 2026
[j33]Weide Liu, Zhonghua Wu, Henghui Ding, Fayao Liu, Jie Lin, Guosheng Lin, Wei Zhou:
Exploiting independent query information for few-shot image segmentation. Displays 91: 103179 (2026)- 2025
- [j32]Tianyi Zhang, Chunyun Chen, Yun Liu, Xue Geng, Mohamed M. Sabry Aly, Jie Lin:
PSRR-MaxpoolNMS++: Fast Non-Maximum Suppression With Discretization and Pooling. IEEE Trans. Pattern Anal. Mach. Intell. 47(2): 978-993 (2025) - [j31]Kaixin Xu, Zhe Wang, Runtao Huang, Xue Geng, Jie Lin, Xulei Yang, Min Wu, Xiaoli Li, Weisi Lin:
Efficient Distortion-Minimized Layerwise Pruning. IEEE Trans. Pattern Anal. Mach. Intell. 47(10): 9298-9315 (2025) - [j30]Xue Geng, Zhe Wang, Chunyun Chen, Qing Xu, Kaixin Xu, Jin Chao, Manas Gupta, Xulei Yang, Zhenghua Chen, Mohamed M. Sabry Aly, Jie Lin, Min Wu, Xiaoli Li:
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 36(4): 5837-5857 (2025) - 2024
- [j29]Chenjing Liu, Xiangru Chen, Jie Lin, Peng Hu, Junfeng Wang, Xue Geng:
Evolving masked low-rank transformer for long text understanding. Appl. Soft Comput. 152: 111207 (2024) - [j28]Xiangru Chen, Chenjing Liu, Peng Hu, Jie Lin, Yunhong Gong, Yingke Chen, Dezhong Peng, Xue Geng:
Adaptive Masked Autoencoder Transformer for image classification. Appl. Soft Comput. 164: 111958 (2024) - [j27]Xiangru Chen, Chenjing Liu, Peng Hu, Jie Lin, Yunhong Gong, Yingke Chen, Dezhong Peng, Xue Geng:
Evolving filter criteria for randomly initialized network pruning in image classification. Neurocomputing 594: 127872 (2024) - [j26]Weide Liu, Zhonghua Wu, Yiming Wang, Henghui Ding, Fayao Liu, Jie Lin, Guosheng Lin:
LCReg: Long-tailed image classification with Latent Categories based Recognition. Pattern Recognit. 145: 109971 (2024) - [j25]Peng Hu, Liangli Zhen, Xi Peng, Hongyuan Zhu, Jie Lin, Xu Wang, Dezhong Peng:
Deep Supervised Multi-View Learning With Graph Priors. IEEE Trans. Image Process. 33: 123-133 (2024) - [j24]Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan Sheng Foo:
On Representation Knowledge Distillation for Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4656-4667 (2024) - [c55]Kaixin Xu, Zhe Wang, Chunyun Chen, Xue Geng, Jie Lin, Xulei Yang, Min Wu, Xiaoli Li, Weisi Lin:
LPViT: Low-Power Semi-structured Pruning for Vision Transformers. ECCV (71) 2024: 269-287 - [c54]Manas Gupta, Efe Camci, Vishandi Rudy Keneta, Abhishek Vaidyanathan, Ritwik Kanodia, Ashish James, Chuan-Sheng Foo, Min Wu, Jie Lin:
Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning. CAI 2024: 747-754 - [i34]Xue Geng, Zhe Wang, Chunyun Chen, Qing Xu, Kaixin Xu, Chao Jin, Manas Gupta, Xulei Yang, Zhenghua Chen, Mohamed M. Sabry Aly, Jie Lin, Min Wu, Xiaoli Li:
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks. CoRR abs/2405.06038 (2024) - [i33]Kaixin Xu, Zhe Wang, Chunyun Chen, Xue Geng, Jie Lin, Xulei Yang, Min Wu, Xiaoli Li, Weisi Lin:
LPViT: Low-Power Semi-structured Pruning for Vision Transformers. CoRR abs/2407.02068 (2024) - 2023
- [j23]Peng Hu, Hongyuan Zhu, Jie Lin, Dezhong Peng, Yin-Ping Zhao, Xi Peng:
Unsupervised Contrastive Cross-Modal Hashing. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3877-3889 (2023) - [i32]Ruibing Jin, Guosheng Lin, Min Wu, Jie Lin, Zhengguo Li, Xiaoli Li, Zhenghua Chen:
Unlimited Knowledge Distillation for Action Recognition in the Dark. CoRR abs/2308.09327 (2023) - [i31]Kaixin Xu, Zhe Wang, Xue Geng, Jie Lin, Min Wu, Xiaoli Li, Weisi Lin:
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks. CoRR abs/2308.10438 (2023) - [i30]Weide Liu, Zhonghua Wu, Yiming Wang, Henghui Ding, Fayao Liu, Jie Lin, Guosheng Lin:
LCReg: Long-Tailed Image Classification with Latent Categories based Recognition. CoRR abs/2309.07186 (2023) - 2022
- [j22]Souhail Meftah, Benjamin Hong Meng Tan, Khin Mi Mi Aung, Yuxiao Lu, Jie Lin, Bharadwaj Veeravalli:
Towards high performance homomorphic encryption for inference tasks on CPU: An MPI approach. Future Gener. Comput. Syst. 134: 13-21 (2022) - [j21]Efe Camci, Manas Gupta, Min Wu, Jie Lin:
QLP: Deep Q-Learning for Pruning Deep Neural Networks. IEEE Trans. Circuits Syst. Video Technol. 32(10): 6488-6501 (2022) - [j20]Peng Hu, Xi Peng, Hongyuan Zhu, Liangli Zhen, Jie Lin, Huaibai Yan, Dezhong Peng:
Deep Semisupervised Multiview Learning With Increasing Views. IEEE Trans. Cybern. 52(12): 12954-12965 (2022) - [j19]Huijing Zhan, Jie Lin, Kenan Emir Ak, Boxin Shi, Ling-Yu Duan, Alex C. Kot:
$A^3$-FKG: Attentive Attribute-Aware Fashion Knowledge Graph for Outfit Preference Prediction. IEEE Trans. Multim. 24: 819-831 (2022) - [c53]Fayao Liu, Guosheng Lin, Chuan-Sheng Foo, Chaitanya K. Joshi, Jie Lin:
Point Discriminative Learning for Data-efficient 3D Point Cloud Analysis. 3DV 2022: 42-51 - [c52]Chunyun Chen, Tianyi Zhang, Zehui Yu, Adithi Raghuraman, Shwetalaxmi Udayan, Jie Lin, Mohamed M. Sabry Aly:
Scalable Hardware Acceleration of Non-Maximum Suppression. DATE 2022: 96-99 - [c51]Zhe Wang, Jie Lin, Xue Geng, Mohamed M. Sabry Aly, Vijay Chandrasekhar:
RDO-Q: Extremely Fine-Grained Channel-Wise Quantization via Rate-Distortion Optimization. ECCV (12) 2022: 157-172 - [c50]Wei Wang, Zhuo Chen, Zhe Wang, Jie Lin, Long Xu, Weisi Lin:
Channel-Wise Bit Allocation for Deep Visual Feature Quantization. ICIP 2022: 3978-3982 - [i29]Peng Hu, Xi Peng, Hongyuan Zhu, Mohamed M. Sabry Aly, Jie Lin:
OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization. CoRR abs/2205.11141 (2022) - [i28]Weide Liu, Zhonghua Wu, Yiming Wang, Henghui Ding, Fayao Liu, Jie Lin, Guosheng Lin:
Long-tailed Recognition by Learning from Latent Categories. CoRR abs/2206.01010 (2022) - [i27]Manas Gupta, Efe Camci, Vishandi Rudy Keneta, Abhishek Vaidyanathan, Ritwik Kanodia, Chuan-Sheng Foo, Min Wu, Jie Lin:
Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning. CoRR abs/2209.14624 (2022) - 2021
- [j18]Peng Hu, Xi Peng, Hongyuan Zhu, Jie Lin, Liangli Zhen, Wei Wang, Dezhong Peng:
Cross-modal discriminant adversarial network. Pattern Recognit. 112: 107734 (2021) - [j17]Peng Hu, Xi Peng, Hongyuan Zhu, Jie Lin, Liangli Zhen, Dezhong Peng:
Joint Versus Independent Multiview Hashing for Cross-View Retrieval. IEEE Trans. Cybern. 51(10): 4982-4993 (2021) - [j16]Ahmad Al Badawi, Chao Jin, Jie Lin, Chan Fook Mun, Sim Jun Jie, Benjamin Hong Meng Tan, Xiao Nan, Khin Mi Mi Aung, Vijay Ramaseshan Chandrasekhar:
Towards the AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data With GPUs. IEEE Trans. Emerg. Top. Comput. 9(3): 1330-1343 (2021) - [j15]Huijing Zhan, Chenyu Yi, Boxin Shi, Jie Lin, Ling-Yu Duan, Alex C. Kot:
Pose-Normalized and Appearance-Preserved Street-to-Shop Clothing Image Generation and Feature Learning. IEEE Trans. Multim. 23: 133-144 (2021) - [j14]Qianli Xu, Ana Garcia del Molino, Jie Lin, Fen Fang, Vigneshwaran Subbaraju, Liyuan Li, Joo-Hwee Lim:
Lifelog Image Retrieval Based on Semantic Relevance Mapping. ACM Trans. Multim. Comput. Commun. Appl. 17(3): 92:1-92:18 (2021) - [j13]Ahmad Al Badawi, Bharadwaj Veeravalli, Jie Lin, Xiao Nan, Kazuaki Matsumura, Khin Mi Mi Aung:
Multi-GPU Design and Performance Evaluation of Homomorphic Encryption on GPU Clusters. IEEE Trans. Parallel Distributed Syst. 32(2): 379-391 (2021) - [c49]Peng Hu, Xi Peng, Hongyuan Zhu, Mohamed M. Sabry Aly, Jie Lin:
OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization. AAAI 2021: 7780-7788 - [c48]Peng Hu, Xi Peng, Hongyuan Zhu, Liangli Zhen, Jie Lin:
Learning Cross-Modal Retrieval With Noisy Labels. CVPR 2021: 5403-5413 - [c47]Tianyi Zhang, Jie Lin, Peng Hu, Bin Zhao, Mohamed M. Sabry Aly:
PSRR-MaxpoolNMS: Pyramid Shifted MaxpoolNMS With Relationship Recovery. CVPR 2021: 15840-15848 - [c46]Chunyun Chen, Zhe Wang, Xiaowei Chen, Jie Lin, Mohamed M. Sabry Aly:
Efficient Tunstall Decoder for Deep Neural Network Compression. DAC 2021: 1021-1026 - [c45]Wang Zhe, Jie Lin, Mohamed M. Sabry Aly, Sean I. Young, Vijay Chandrasekhar, Bernd Girod:
Rate-Distortion Optimized Coding for Efficient CNN Compression. DCC 2021: 253-262 - [c44]Huijing Zhan, Jie Lin:
PAN: Personalized Attention Network For Outfit Recommendation. ICIP 2021: 2663-2667 - [i26]Govind Narasimman, Kangkang Lu, Arun Raja, Chuan Sheng Foo, Mohamed M. Sabry Aly, Jie Lin, Vijay Chandrasekhar:
A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity Recognition. CoRR abs/2101.04859 (2021) - [i25]Yuxiao Lu, Jie Lin, Chao Jin, Zhe Wang, Khin Mi Mi Aung, Xiaoli Li:
FFConv: Fast Factorized Neural Network Inference on Encrypted Data. CoRR abs/2102.03494 (2021) - [i24]Tianyi Zhang, Jie Lin, Peng Hu, Bin Zhao, Mohamed M. Sabry Aly:
PSRR-MaxpoolNMS: Pyramid Shifted MaxpoolNMS with Relationship Recovery. CoRR abs/2105.12990 (2021) - [i23]Weide Liu, Zhonghua Wu, Henghui Ding, Fayao Liu, Jie Lin, Guosheng Lin:
Few-Shot Segmentation with Global and Local Contrastive Learning. CoRR abs/2108.05293 (2021) - [i22]Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan-Sheng Foo:
On Representation Knowledge Distillation for Graph Neural Networks. CoRR abs/2111.04964 (2021) - 2020
- [c43]Peng Hu, Hongyuan Zhu, Xi Peng, Jie Lin:
Semi-Supervised Multi-Modal Learning with Balanced Spectral Decomposition. AAAI 2020: 99-106 - [c42]Xue Geng, Jie Lin, Shaohua Li:
Cascaded Mixed-Precision Networks. ICIP 2020: 241-245 - [c41]Li Wang, Ting Liu, Bing Wang, Jie Lin, Xulei Yang, Gang Wang:
Object Tracking Via ImageNet Classification Scores. ICIP 2020: 2101-2105 - [c40]Quang-Hieu Pham, Pierre Sevestre, Ramanpreet Singh Pahwa, Huijing Zhan, Chun Ho Pang, Yuda Chen, Armin Mustafa, Vijay Chandrasekhar, Jie Lin:
A*3D Dataset: Towards Autonomous Driving in Challenging Environments. ICRA 2020: 2267-2273 - [i21]Jie Fu, Xue Geng, Zhijian Duan, Bohan Zhuang, Xingdi Yuan, Adam Trischler, Jie Lin, Chris Pal, Hao Dong:
Role-Wise Data Augmentation for Knowledge Distillation. CoRR abs/2004.08861 (2020) - [i20]Manas Gupta, Siddharth Aravindan, Aleksandra Kalisz, Vijay Chandrasekhar, Jie Lin:
Learning to Prune Deep Neural Networks via Reinforcement Learning. CoRR abs/2007.04756 (2020)
2010 – 2019
- 2019
- [j12]Ling-Yu Duan, Yihang Lou, Yan Bai, Tiejun Huang, Wen Gao, Vijay Chandrasekhar, Jie Lin, Shiqi Wang, Alex ChiChung Kot:
Compact Descriptors for Video Analysis: The Emerging MPEG Standard. IEEE Multim. 26(2): 44-54 (2019) - [j11]Zhaoqiang Xia, Jie Lin, Xiaoyi Feng:
Trademark image retrieval via transformation-invariant deep hashing. J. Vis. Commun. Image Represent. 59: 108-116 (2019) - [j10]Yuwei Wu, Feng Gao, Yicheng Huang, Jie Lin, Vijay Chandrasekhar, Junsong Yuan, Ling-Yu Duan:
Codebook-Free Compact Descriptor for Scalable Visual Search. IEEE Trans. Multim. 21(2): 388-401 (2019) - [c39]Lile Cai, Bin Zhao, Zhe Wang, Jie Lin, Chuan Sheng Foo, Mohamed M. Sabry Aly, Vijay Chandrasekhar:
MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors. CVPR 2019: 9356-9364 - [c38]Xue Geng, Jie Fu, Bin Zhao, Jie Lin, Mohamed M. Sabry Aly, Christopher J. Pal, Vijay Chandrasekhar:
Dataflow-Based Joint Quantization for Deep Neural Networks. DCC 2019: 574 - [c37]Zhuo Chen, Jie Lin, Zhe Wang, Vijay Chandrasekhar, Weisi Lin:
Beyond Ranking Loss: Deep Holographic Networks for Multi-Label Video Search. ICIP 2019: 879-883 - [c36]Li Wang, Ting Liu, Bing Wang, Jie Lin, Xulei Yang, Gang Wang:
Learning Hierarchical Features for Visual Object Tracking With Recursive Neural Networks. ICIP 2019: 3088-3092 - [c35]Wang Zhe, Jie Lin, Vijay Chandrasekhar, Bernd Girod:
Optimizing the Bit Allocation for Compression of Weights and Activations of Deep Neural Networks. ICIP 2019: 3826-3830 - [c34]Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry Aly:
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. ISLPED 2019: 1-6 - [i19]Xue Geng, Jie Fu, Bin Zhao, Jie Lin, Mohamed M. Sabry Aly, Christopher J. Pal, Vijay Chandrasekhar:
Dataflow-based Joint Quantization of Weights and Activations for Deep Neural Networks. CoRR abs/1901.02064 (2019) - [i18]Jin Chao, Ahmad Al Badawi, Balagopal Unnikrishnan, Jie Lin, Chan Fook Mun, James M. Brown, J. Peter Campbell, Michael F. Chiang, Jayashree Kalpathy-Cramer, Vijay Ramaseshan Chandrasekhar, Pavitra Krishnaswamy, Khin Mi Mi Aung:
CaRENets: Compact and Resource-Efficient CNN for Homomorphic Inference on Encrypted Medical Images. CoRR abs/1901.10074 (2019) - [i17]Quang-Hieu Pham, Pierre Sevestre, Ramanpreet Singh Pahwa, Huijing Zhan, Chun Ho Pang, Yuda Chen, Armin Mustafa, Vijay Chandrasekhar, Jie Lin:
A*3D Dataset: Towards Autonomous Driving in Challenging Environments. CoRR abs/1909.07541 (2019) - 2018
- [c33]Xue Geng, Jie Lin, Bin Zhao, Anmin Kong, Mohamed M. Sabry Aly, Vijay Chandrasekhar:
Hardware-Aware Softmax Approximation for Deep Neural Networks. ACCV (4) 2018: 107-122 - [c32]Ziqian Chen, Jie Lin, Vijay Chandrasekhar, Ling-Yu Duan:
Gated Square-Root Pooling for Image Instance Retrieval. ICIP 2018: 1982-1986 - [i16]Ahmad Al Badawi, Jin Chao, Jie Lin, Chan Fook Mun, Sim Jun Jie, Benjamin Hong Meng Tan, Xiao Nan, Khin Mi Mi Aung, Vijay Ramaseshan Chandrasekhar:
The AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs. CoRR abs/1811.00778 (2018) - [i15]Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry:
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. CoRR abs/1811.12065 (2018) - [i14]Ahmad Al Badawi, Jin Chao, Jie Lin, Chan Fook Mun, Sim Jun Jie, Benjamin Hong Meng Tan, Xiao Nan, Khin Mi Mi Aung, Vijay Ramaseshan Chandrasekhar:
The AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs. IACR Cryptol. ePrint Arch. 2018: 1056 (2018) - 2017
- [j9]Sai Manoj Prakhya, Jie Lin, Vijay Chandrasekhar, Weisi Lin, Bingbing Liu:
3DHoPD: A Fast Low-Dimensional 3-D Descriptor. IEEE Robotics Autom. Lett. 2(3): 1472-1479 (2017) - [j8]Sai Manoj Prakhya, Weisi Lin, Vijay Chandrasekhar, Bingbing Liu, Jie Lin:
Low Bit-rate 3D feature descriptors for depth data from Kinect-style sensors. Signal Process. Image Commun. 51: 40-49 (2017) - [j7]Zhaoqiang Xia, Xiaoyi Feng, Jie Lin, Abdenour Hadid:
Deep convolutional hashing using pairwise multi-label supervision for large-scale visual search. Signal Process. Image Commun. 59: 109-116 (2017) - [j6]Bappaditya Mandal, Liyuan Li, Gang Sam Wang, Jie Lin:
Towards Detection of Bus Driver Fatigue Based on Robust Visual Analysis of Eye State. IEEE Trans. Intell. Transp. Syst. 18(3): 545-557 (2017) - [j5]Jie Lin, Ling-Yu Duan, Shiqi Wang, Yan Bai, Yihang Lou, Vijay Chandrasekhar, Tiejun Huang, Alex ChiChung Kot, Wen Gao:
HNIP: Compact Deep Invariant Representations for Video Matching, Localization, and Retrieval. IEEE Trans. Multim. 19(9): 1968-1983 (2017) - [c31]Olivier Morère, Antoine Veillard, Jie Lin, Julie Petta, Vijay Chandrasekhar, Tomaso A. Poggio:
Group Invariant Deep Representations for Image Instance Retrieval. AAAI Spring Symposia 2017 - [c30]Ana Garcia del Molino, Bappaditya Mandal, Jie Lin, Joo-Hwee Lim, Vigneshwaran Subbaraju, Vijay Chandrasekhar:
VC-I2R@ImageCLEF2017: Ensemble of Deep Learned Features for Lifelog Video Summarization. CLEF (Working Notes) 2017 - [c29]Vijay Chandrasekhar, Jie Lin, Qianli Liao, Olivier Morère, Antoine Veillard, Ling-Yu Duan, Tomaso A. Poggio:
Compression of Deep Neural Networks for Image Instance Retrieval. DCC 2017: 300-309 - [c28]Yihang Lou, Yan Bai, Jie Lin, Shiqi Wang, Jie Chen, Vijay Chandrasekhar, Ling-Yu Duan, Tiejun Huang, Alex ChiChung Kot, Wen Gao:
Compact Deep Invariant Descriptors for Video Retrieval. DCC 2017: 420-429 - [c27]Yan Bai, Jie Lin, Vijay Chandrasekhar, Yihang Lou, Shiqi Wang, Ling-Yu Duan, Tiejun Huang, Alex C. Kot:
Deep regional feature pooling for video matching. ICIP 2017: 380-384 - [c26]Yicheng Huang, Ling-Yu Duan, Zhe Wang, Jie Lin, Vijay Chandrasekhar, Tiejun Huang:
A Multi-Block N-ary trie structure for exact r-neighbour search in hamming space. ICIP 2017: 1117-1121 - [c25]Kingsley Kuan, Gaurav Manek, Jie Lin, Yuan Fang, Vijay Chandrasekhar:
Region average pooling for context-aware object detection. ICIP 2017: 1347-1351 - [c24]Yuan Fang, Kingsley Kuan, Jie Lin, Cheston Tan, Vijay Chandrasekhar:
Object Detection Meets Knowledge Graphs. IJCAI 2017: 1661-1667 - [c23]Jie Lin, Olivier Morère, Antoine Veillard, Ling-Yu Duan, Hanlin Goh, Vijay Chandrasekhar:
DeepHash for Image Instance Retrieval: Getting Regularization, Depth and Fine-Tuning Right. ICMR 2017: 133-141 - [c22]Olivier Morère, Jie Lin, Antoine Veillard, Ling-Yu Duan, Vijay Chandrasekhar, Tomaso A. Poggio:
Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval. ICMR 2017: 260-268 - [c21]Jie Lin, Ana Garcia del Molino, Qianli Xu, Fen Fang, Vigneshwaran Subbaraju, Joo-Hwee Lim, Liyuan Li, Vijay Chandrasekhar:
VCI2R at the NTCIR-13 Lifelog-2 Lifelog Semantic Access Task. NTCIR 2017 - [c20]Qianli Xu, Vigneshwaran Subbaraju, Ana Garcia del Molino, Jie Lin, Fen Fang, Joo-Hwee Lim, Liyuan Li, Vijay Chandrasekhar:
Visualizing Personal Lifelog Data for Deeper Insights at the NTCIR-13 Lifelog-2 Task. NTCIR 2017 - [i13]Vijay Chandrasekhar, Jie Lin, Qianli Liao, Olivier Morère, Antoine Veillard, Ling-Yu Duan, Tomaso A. Poggio:
Compression of Deep Neural Networks for Image Instance Retrieval. CoRR abs/1701.04923 (2017) - [i12]Ling-Yu Duan, Vijay Chandrasekhar, Shiqi Wang, Yihang Lou, Jie Lin, Yan Bai, Tiejun Huang, Alex ChiChung Kot, Wen Gao:
Compact Descriptors for Video Analysis: the Emerging MPEG Standard. CoRR abs/1704.08141 (2017) - [i11]Kingsley Kuan, Mathieu Ravaut, Gaurav Manek, Huiling Chen, Jie Lin, Babar Nazir, Cen Chen, Tse Chiang Howe, Zeng Zeng, Vijay Chandrasekhar:
Deep Learning for Lung Cancer Detection: Tackling the Kaggle Data Science Bowl 2017 Challenge. CoRR abs/1705.09435 (2017) - [i10]Zhe Wang, Kingsley Kuan, Mathieu Ravaut, Gaurav Manek, Sibo Song, Fang Yuan, Kim Seokhwan, Nancy F. Chen, Luis Fernando D'Haro, Anh Tuan Luu, Hongyuan Zhu, Zeng Zeng, Ngai-Man Cheung, Georgios Piliouras, Jie Lin, Vijay Chandrasekhar:
Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text. CoRR abs/1706.05461 (2017) - [i9]Gaurav Manek, Jie Lin, Vijay Chandrasekhar, Lingyu Duan, Sateesh Giduthuri, Xiaoli Li, Tomaso A. Poggio:
Pruning Convolutional Neural Networks for Image Instance Retrieval. CoRR abs/1707.05455 (2017) - [i8]Fang Yuan, Zhe Wang, Jie Lin, Luis Fernando D'Haro, Jung-Jae Kim, Zeng Zeng, Vijay Chandrasekhar:
End-to-End Video Classification with Knowledge Graphs. CoRR abs/1711.01714 (2017) - 2016
- [j4]Vijay Chandrasekhar, Jie Lin, Olivier Morère, Hanlin Goh, Antoine Veillard:
A practical guide to CNNs and Fisher Vectors for image instance retrieval. Signal Process. 128: 426-439 (2016) - [j3]Ling-Yu Duan, Vijay Chandrasekhar, Jie Chen, Jie Lin, Zhe Wang, Tiejun Huang, Bernd Girod, Wen Gao:
Overview of the MPEG-CDVS Standard. IEEE Trans. Image Process. 25(1): 179-194 (2016) - [c19]Jie Lin, Olivier Morère, Julie Petta, Vijay Chandrasekhar, Antoine Veillard:
Tiny Descriptors for Image Retrieval with Unsupervised Triplet Hashing. DCC 2016: 397-406 - [c18]Sibo Song, Ngai-Man Cheung, Vijay Chandrasekhar, Bappaditya Mandal, Jie Lin:
Egocentric activity recognition with multimodal fisher vector. ICASSP 2016: 2717-2721 - [i7]Olivier Morère, Antoine Veillard, Jie Lin, Julie Petta, Vijay Chandrasekhar, Tomaso A. Poggio:
Group Invariant Deep Representations for Image Instance Retrieval. CoRR abs/1601.02093 (2016) - [i6]Sibo Song, Ngai-Man Cheung, Vijay Chandrasekhar, Bappaditya Mandal, Jie Lin:
Egocentric Activity Recognition with Multimodal Fisher Vector. CoRR abs/1601.06603 (2016) - [i5]Olivier Morère, Jie Lin, Antoine Veillard, Vijay Chandrasekhar:
Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval. CoRR abs/1603.04595 (2016) - 2015
- [j2]Ling-Yu Duan, Jie Lin, Zhe Wang, Tiejun Huang, Wen Gao:
Weighted Component Hashing of Binary Aggregated Descriptors for Fast Visual Search. IEEE Trans. Multim. 17(6): 828-842 (2015) - [c17]Jie Lin, Zhe Wang, Yitong Wang, Vijay Chandrasekhar, Liyuan Li:
Selective aggregated descriptors for robust mobile image retrieval. APSIPA 2015: 169-177 - [c16]Vijay Chandrasekhar, Jie Lin, Olivier Morère, Antoine Veillard, Hanlin Goh:
Compact Global Descriptors for Visual Search. DCC 2015: 333-342 - [c15]Zhe Wang, Ling-Yu Duan, Jie Lin, Jie Chen, Tiejun Huang, Wen Gao:
Optimizing Binary Fisher Codes for Visual Search. DCC 2015: 475 - [c14]Olivier Morère, Hanlin Goh, Antoine Veillard, Vijay Chandrasekhar, Jie Lin:
Co-regularized deep representations for video summarization. ICIP 2015: 3165-3169 - [c13]Zhangshuai Huang, Ling-Yu Duan, Jie Lin, Shiqi Wang, Siwei Ma, Tiejun Huang:
An efficient coding framework for compact descriptors extracted from video sequence. ICIP 2015: 3822-3826 - [c12]Yitong Wang, Ling-Yu Duan, Jie Lin, Zhe Wang, Tiejun Huang:
Hierarchical multi-VLAD for image retrieval. ICIP 2015: 4629-4633 - [c11]Zhe Wang, Ling-Yu Duan, Jie Lin, Xiaofang Wang, Tiejun Huang, Wen Gao:
Hamming Compatible Quantization for Hashing. IJCAI 2015: 2298-2304 - [i4]Jie Lin, Olivier Morère, Vijay Chandrasekhar, Antoine Veillard, Hanlin Goh:
DeepHash: Getting Regularization, Depth and Fine-Tuning Right. CoRR abs/1501.04711 (2015) - [i3]Olivier Morère, Hanlin Goh, Antoine Veillard, Vijay Chandrasekhar, Jie Lin:
Co-Regularized Deep Representations for Video Summarization. CoRR abs/1501.07738 (2015) - [i2]Vijay Chandrasekhar, Jie Lin, Olivier Morère, Hanlin Goh, Antoine Veillard:
A Practical Guide to CNNs and Fisher Vectors for Image Instance Retrieval. CoRR abs/1508.02496 (2015) - [i1]Jie Lin, Olivier Morère, Julie Petta, Vijay Chandrasekhar, Antoine Veillard:
Tiny Descriptors for Image Retrieval with Unsupervised Triplet Hashing. CoRR abs/1511.03055 (2015) - 2014
- [j1]Ling-Yu Duan, Jie Lin, Jie Chen, Tiejun Huang, Wen Gao:
Compact Descriptors for Visual Search. IEEE Multim. 21(3): 30-40 (2014) - [c10]Zhe Wang, Ling-Yu Duan, Jie Lin, Tiejun Huang, Wen Gao, Miroslaw Bober:
Component hashing of variable-length binary aggregated descriptors for fast image search. ICIP 2014: 2217-2221 - [c9]Yitong Wang, Ling-Yu Duan, Jie Lin, Tiejun Huang, Wen Gao:
Joint optimization of JPEG quantization table and coefficient thresholding for low bitrate mobile visual search. ICIP 2014: 3978-3982 - 2013
- [c8]Jie Lin, Ling-Yu Duan, Tiejun Huang, Wen Gao:
Robust fisher codes for large scale image retrieval. ICASSP 2013: 1513-1517 - [c7]Jie Chen, Ling-Yu Duan, Jie Lin, Rongrong Ji, Tiejun Huang, Wen Gao:
On the interoperability of local descriptors compression. ICASSP 2013: 1518-1522 - [c6]Shuang Yang, Ling-Yu Duan, Jie Lin, Tiejun Huang:
A novel pair-wise image matching strategy with compact descriptors. ICIP 2013: 2572-2576 - [c5]Ling-Yu Duan, Feng Gao, Jie Chen, Jie Lin, Tiejun Huang:
Compact descriptors for mobile visual search and MPEG CDVS standardization. ISCAS 2013: 885-888 - 2012
- [c4]Jie Lin, Ling-Yu Duan, Jie Chen, Rongrong Ji, Siwei Luo, Wen Gao:
Learning multiple codebooks for low bit rate mobile visual search. ICASSP 2012: 933-936 - [c3]Bing Li, Ling-Yu Duan, Jie Lin, Tiejun Huang:
Allocating images and selecting image collections for distributed visual search. ICIMCS 2012: 127-131 - [c2]Jie Lin, Ling-Yu Duan, Junsong Yuan, Qingyong Li, Siwei Luo:
Learning sparse tag patterns for social image classification. ICIP 2012: 2881-2884 - [c1]Jie Lin, Junsong Yuan, Ling-Yu Duan, Siwei Luo, Wen Gao:
Social Image Tagging by Mining Sparse Tag Patterns from Auxiliary Data. ICME 2012: 7-12
Coauthor Index
Vijay Chandrasekhar 0001
aka: Vijay Ramaseshan Chandrasekhar
aka: Vijay Ramaseshan Chandrasekhar
[c51] [j16] [c45] [i26] [c40] [i20] [j12] [j10] [c39] [c38] [c37] [c35] [c34] [i19] [i18] [i17] [c33] [c32] [i16] [i15] [i14] [j9] [j8] [j5] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [i13] [i12] [i11] [i10] [i9] [i8] [j4] [j3] [c19] [c18] [i7] [i6] [i5] [c17] [c16] [c14] [i4] [i3] [i2] [i1]
Ling-Yu Duan
aka: Lingyu Duan
aka: Lingyu Duan
Mohamed M. Sabry
aka: Mohamed M. Sabry Aly
aka: Mohamed M. Sabry Aly
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