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ORCIDVijay Chandrasekhar 0001
Vijay Ramaseshan Chandrasekhar
Person information
- affiliation: A*STAR, Institute for Infocomm Research, Singapore
- affiliation (PhD 2013): Stanford University, CA, United States
- affiliation: Google Inc., Mountain View, CA, USA
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2020 – today
- 2022
[j20]Saisubramaniam Gopalakrishnan
, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi:
Classify and generate: Using classification latent space representations for image generations. Neurocomputing 471: 296-334 (2022)- [c78]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 - [c77]Yasin Yazici, Bruno Lecouat, Kim-Hui Yap, Stefan Winkler, Georgios Piliouras, Vijay Chandrasekhar, Chuan-Sheng Foo:
Mixed Membership Generative Adversarial Networks. ICIP 2022: 1026-1030 - [c76]Lining Zhang, Salahuddin Raju, Ashish James, Rahul Dutta, Gregoire Fournier, Damien Lancry, Kevin Chai Tshun Chuan, Vijay Ramaseshan Chandrasekhar, Chuan Sheng Foo:
Bayesian Deep Active Learning for Analog Circuit Performance Classification. ISCAS 2022: 3018-3022 - 2021
- [j19]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) - [j18]Souhail Meftah, Benjamin Hong Meng Tan, Chan Fook Mun, Khin Mi Mi Aung, Bharadwaj Veeravalli, Vijay Chandrasekhar:
DOReN: Toward Efficient Deep Convolutional Neural Networks with Fully Homomorphic Encryption. IEEE Trans. Inf. Forensics Secur. 16: 3740-3752 (2021) - [c75]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 - [i38]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) - 2020
- [j17]Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar:
Holistic Multi-Modal Memory Network for Movie Question Answering. IEEE Trans. Image Process. 29: 489-499 (2020) - [c74]Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar:
Empirical Analysis Of Overfitting And Mode Drop In Gan Training. ICIP 2020: 1651-1655 - [c73]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 - [i37]Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi:
Classification Representations Can be Reused for Downstream Generations. CoRR abs/2004.07543 (2020) - [i36]Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar:
Empirical Analysis of Overfitting and Mode Drop in GAN Training. CoRR abs/2006.14265 (2020) - [i35]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
- [j16]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) - [j15]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) - [c72]Arko Dutt, Govind Narasimman, Lin Jie, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry:
EAST-DNN: Expediting architectural SimulaTions using deep neural networks: work-in-progress. CODES+ISSS 2019: 4:1-4:2 - [c71]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 - [c70]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 - [c69]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 - [c68]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 - [c67]Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras:
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile. ICLR (Poster) 2019 - [c66]Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar:
The Unusual Effectiveness of Averaging in GAN Training. ICLR (Poster) 2019 - [c65]Kangkang Lu, Chuan-Sheng Foo, Kah Kuan Teh, Huy Dat Tran, Vijay Ramaseshan Chandrasekhar:
Semi-Supervised Audio Classification with Consistency-Based Regularization. INTERSPEECH 2019: 3654-3658 - [c64]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 - [c63]Ramanpreet Singh Pahwa, Vijay Ramaseshan Chandrasekhar, Jin Chao, Jestine Paul, Yiqun Li, Ma Tin Lay Nwe, Shudong Xie, Ashish James, Arulmurugan Ambikapathi, Zeng Zeng:
FaultNet: Faulty Rail-Valves Detection using Deep Learning and Computer Vision. ITSC 2019: 559-566 - [c62]Khalil Ouardini, Huijuan Yang, Balagopal Unnikrishnan, Manon Romain, Camille Garcin, Houssam Zenati, J. Peter Campbell, Michael F. Chiang, Jayashree Kalpathy-Cramer, Vijay Chandrasekhar, Pavitra Krishnaswamy, Chuan-Sheng Foo:
Towards Practical Unsupervised Anomaly Detection on Retinal Images. DART/MIL3ID@MICCAI 2019: 225-234 - [c61]Rahul Dutta, Salahuddin Raju, Ashish James, Leo John Chemmanda, Yong-Joon Jeon, Balagopal Unnikrishnan, Chuan Sheng Foo, Zeng Zeng, Kevin Tshun Chuan Chai, Vijay Ramaseshan Chandrasekhar:
Learning of Multi-Dimensional Analog Circuits Through Generative Adversarial Network (GAN). SoCC 2019: 394-399 - [i34]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) - [i33]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) - [i32]Yasin Yazici, Bruno Lecouat, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar:
Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions. CoRR abs/1902.03444 (2019) - [i31]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) - [i30]Ramanpreet Singh Pahwa, Jin Chao, Jestine Paul, Yiqun Li, Ma Tin Lay Nwe, Shudong Xie, Ashish James, Arulmurugan Ambikapathi, Zeng Zeng, Vijay Ramaseshan Chandrasekhar:
FaultNet: Faulty Rail-Valves Detection using Deep Learning and Computer Vision. CoRR abs/1912.04219 (2019) - 2018
- [c60]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 - [c59]Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar:
Adversarially Learned Anomaly Detection. ICDM 2018: 727-736 - [c58]Ziqian Chen, Jie Lin, Vijay Chandrasekhar, Ling-Yu Duan:
Gated Square-Root Pooling for Image Instance Retrieval. ICIP 2018: 1982-1986 - [c57]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar:
Semi-Supervised Learning With GANs: Revisiting Manifold Regularization. ICLR (Workshop) 2018 - [c56]Hongyuan Zhu, Xi Peng, Vijay Chandrasekhar, Liyuan Li, Joo-Hwee Lim:
DehazeGAN: When Image Dehazing Meets Differential Programming. IJCAI 2018: 1234-1240 - [c55]Xulei Yang, Zeng Zeng, Sin G. Teo, Li Wang, Vijay Chandrasekhar, Steven C. H. Hoi:
Deep Learning for Practical Image Recognition: Case Study on Kaggle Competitions. KDD 2018: 923-931 - [c54]Sibo Song, Ngai-Man Cheung, Vijay Chandrasekhar, Bappaditya Mandal:
Deep Adaptive Temporal Pooling for Activity Recognition. ACM Multimedia 2018: 1829-1837 - [i29]Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar:
Efficient GAN-Based Anomaly Detection. CoRR abs/1802.06222 (2018) - [i28]Savitha Ramasamy, Kanagasabai Rajaraman, Pavitra Krishnaswamy, Vijay Chandrasekhar:
Online Deep Learning: Growing RBM on the fly. CoRR abs/1803.02043 (2018) - [i27]Juan Pablo Correa-Baena, Kedar Hippalgaonkar, Jeroen van Duren, Shaffiq Jaffer, Vijay Ramaseshan Chandrasekhar, Vladan Stevanovic, Cyrus Wadia, Supratik Guha, Tonio Buonassisi:
Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing. CoRR abs/1803.11246 (2018) - [i26]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar:
Semi-Supervised Learning with GANs: Revisiting Manifold Regularization. CoRR abs/1805.08957 (2018) - [i25]Yasin Yazici, Chuan Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar:
The Unusual Effectiveness of Averaging in GAN Training. CoRR abs/1806.04498 (2018) - [i24]Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras:
Mirror descent in saddle-point problems: Going the extra (gradient) mile. CoRR abs/1807.02629 (2018) - [i23]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar:
Manifold regularization with GANs for semi-supervised learning. CoRR abs/1807.04307 (2018) - [i22]Sibo Song, Ngai-Man Cheung, Vijay Chandrasekhar, Bappaditya Mandal:
Deep Adaptive Temporal Pooling for Activity Recognition. CoRR abs/1808.07272 (2018) - [i21]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) - [i20]Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar:
Holistic Multi-modal Memory Network for Movie Question Answering. CoRR abs/1811.04595 (2018) - [i19]Léo Laugier, Daniil Bash, Jose Recatala, Hong Kuan Ng, Savitha Ramasamy, Chuan-Sheng Foo, Vijay Ramaseshan Chandrasekhar, Kedar Hippalgaonkar:
Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials. CoRR abs/1811.06219 (2018) - [i18]Minggang Zeng, Jatin Nitin Kumar, Zeng Zeng, Ramasamy Savitha, Vijay Ramaseshan Chandrasekhar, Kedar Hippalgaonkar:
Graph Convolutional Neural Networks for Polymers Property Prediction. CoRR abs/1811.06231 (2018) - [i17]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) - [i16]Houssam Zenati, Manon Romain, Chuan Sheng Foo, Bruno Lecouat, Vijay Ramaseshan Chandrasekhar:
Adversarially Learned Anomaly Detection. CoRR abs/1812.02288 (2018) - [i15]Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy:
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. CoRR abs/1812.07832 (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
- [j14]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) - [j13]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) - [j12]Liyuan Li, Qianli Xu, Vijay Chandrasekhar, Joo-Hwee Lim, Cheston Tan, Michal Mukawa:
A Wearable Virtual Usher for Vision-Based Cognitive Indoor Navigation. IEEE Trans. Cybern. 47(4): 841-854 (2017) - [j11]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) - [c53]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 - [c52]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 - [c51]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 - [c50]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 - [c49]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 - [c48]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 - [c47]Kingsley Kuan, Gaurav Manek, Jie Lin, Yuan Fang, Vijay Chandrasekhar:
Region average pooling for context-aware object detection. ICIP 2017: 1347-1351 - [c46]Yuan Fang, Kingsley Kuan, Jie Lin, Cheston Tan, Vijay Chandrasekhar:
Object Detection Meets Knowledge Graphs. IJCAI 2017: 1661-1667 - [c45]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 - [c44]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 - [c43]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 - [c42]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
- [j10]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) - [j9]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) - [c41]Sibo Song, Vijay Chandrasekhar, Bappaditya Mandal, Liyuan Li, Joo-Hwee Lim, Giduthuri Sateesh Babu, Phyo Phyo San, Ngai-Man Cheung:
Multimodal Multi-Stream Deep Learning for Egocentric Activity Recognition. CVPR Workshops 2016: 378-385 - [c40]Jie Lin, Olivier Morère, Julie Petta, Vijay Chandrasekhar, Antoine Veillard:
Tiny Descriptors for Image Retrieval with Unsupervised Triplet Hashing. DCC 2016: 397-406 - [c39]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
- [c38]Jie Lin, Zhe Wang, Yitong Wang, Vijay Chandrasekhar, Liyuan Li:
Selective aggregated descriptors for robust mobile image retrieval. APSIPA 2015: 169-177 - [c37]Vijay Chandrasekhar, Jie Lin, Olivier Morère, Antoine Veillard, Hanlin Goh:
Compact Global Descriptors for Visual Search. DCC 2015: 333-342 - [c36]Dimosthenis Karatzas, Lluis Gomez-Bigorda, Anguelos Nicolaou, Suman K. Ghosh, Andrew D. Bagdanov, Masakazu Iwamura, Jiri Matas, Lukás Neumann, Vijay Ramaseshan Chandrasekhar, Shijian Lu, Faisal Shafait, Seiichi Uchida, Ernest Valveny:
ICDAR 2015 competition on Robust Reading. ICDAR 2015: 1156-1160 - [c35]Bappaditya Mandal, Liyuan Li, Vijay Chandrasekhar, Joo-Hwee Lim:
Whole space subclass discriminant analysis for face recognition. ICIP 2015: 329-333 - [c34]Olivier Morère, Hanlin Goh, Antoine Veillard, Vijay Chandrasekhar, Jie Lin:
Co-regularized deep representations for video summarization. ICIP 2015: 3165-3169 - [c33]Tian Gan, Yongkang Wong, Bappaditya Mandal, Vijay Chandrasekhar, Mohan S. Kankanhalli:
Multi-sensor Self-Quantification of Presentations. ACM Multimedia 2015: 601-610 - [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
- [j8]Mina Makar, Vijay Chandrasekhar, Sam S. Tsai, David M. Chen, Bernd Girod:
Interframe Coding of Feature Descriptors for Mobile Augmented Reality. IEEE Trans. Image Process. 23(8): 3352-3367 (2014) - [c32]Bappaditya Mandal, Shue-Ching Chia, Liyuan Li, Vijay Chandrasekhar, Cheston Tan, Joo-Hwee Lim:
A Wearable Face Recognition System on Google Glass for Assisting Social Interactions. ACCV Workshops (3) 2014: 419-433 - [c31]Sibo Song, Vijay Chandrasekhar, Ngai-Man Cheung, Sanath Narayan, Liyuan Li, Joo-Hwee Lim:
Activity Recognition in Egocentric Life-Logging Videos. ACCV Workshops (3) 2014: 445-458 - [c30]Cheston Tan, Hanlin Goh, Vijay Chandrasekhar, Liyuan Li, Joo-Hwee Lim:
Understanding the Nature of First-Person Videos: Characterization and Classification Using Low-Level Features. CVPR Workshops 2014: 549-556 - [c29]Vijay Chandrasekhar, Gabriel Takacs, David M. Chen, Sam S. Tsai, Mina Makar, Bernd Girod:
Feature Matching Performance of Compact Descriptors for Visual Search. DCC 2014: 3-12 - [c28]André Araújo, Mina Makar, Vijay Chandrasekhar, David M. Chen, Sam S. Tsai, Huizhong Chen, Roland Angst, Bernd Girod:
Efficient video search using image queries. ICIP 2014: 3082-3086 - [c27]Vijay Chandrasekhar, Cheston Tan, Wu Min, Liyuan Li, Xiaoli Li, Joo-Hwee Lim:
Incremental Graph Clustering for Efficient Retrieval from Streaming Egocentric Video Data. ICPR 2014: 2631-2636 - [c26]Tian Gan, Yongkang Wong, Bappaditya Mandal, Vijay Chandrasekhar, Liyuan Li, Joo-Hwee Lim, Mohan S. Kankanhalli:
Recovering Social Interaction Spatial Structure from Multiple First-Person Views. SAM@MM 2014: 7-12 - 2013
- [j7]Mina Makar, Sam S. Tsai, Vijay Chandrasekhar, David M. Chen, Bernd Girod:
Interframe Coding of Canonical patches for Low Bit-rate Mobile Augmented Reality. Int. J. Semantic Comput. 7(1): 5-24 (2013) - [j6]David M. Chen, Sam S. Tsai, Vijay Chandrasekhar, Gabriel Takacs, Ramakrishna Vedantham, Radek Grzeszczuk, Bernd Girod:
Residual enhanced visual vector as a compact signature for mobile visual search. Signal Process. 93(8): 2316-2327 (2013) - [j5]Gabriel Takacs, Vijay Chandrasekhar, Sam S. Tsai, David M. Chen, Radek Grzeszczuk, Bernd Girod:
Rotation-invariant fast features for large-scale recognition and real-time tracking. Signal Process. Image Commun. 28(4): 334-344 (2013) - [j4]Gabriel Takacs, Vijay Chandrasekhar, Sam S. Tsai, David M. Chen, Radek Grzeszczuk, Bernd Girod:
Fast Computation of Rotation-Invariant Image Features by an Approximate Radial Gradient Transform. IEEE Trans. Image Process. 22(8): 2970-2982 (2013) - 2012
- [j3]Vijay Chandrasekhar, Gabriel Takacs, David M. Chen, Sam S. Tsai, Yuriy A. Reznik, Radek Grzeszczuk, Bernd Girod:
Compressed Histogram of Gradients: A Low-Bitrate Descriptor. Int. J. Comput. Vis. 96(3): 384-399 (2012) - [c25]Mina Makar, Haricharan Lakshman, Vijay Chandrasekhar, Bernd Girod:
Gradient preserving quantization. ICIP 2012: 2505-2508 - [c24]