Publications of DiL Lab

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Pre-prints/Tech-Reports
  1. Bo Zhao, Konda Reddy Mopuri, Hakan Bilen, iDLG: Improved Deep Leakage from Gradients, arXiv preprint arXiv:2001.0261, 2020. [~200 Google Scholar Citations]
Book Chapters
  1. Srinivas S, Sarvadevabhatla R, Konda Reddy Mopuri, Prabhu N, Kruthiventi S and R V Babu, Deep Learning for Medical Image Analysis, Elsevier, January 30, 2017.
Journals
  1. Konda Reddy Mopuri, H. Bilen, N. Tsuchihashi, R. Wada, T. Inoue, K. Kusanagi, T. Nishiyama, H. Tamamura, Early Sign Detection for the Stuck Pipe Scenarios using Unsupervised Deep Learning, in the Journal of Petroleum Science and Engineering, 2022. [Link]. [Impact Factor: 4.35]
  2. Gaurav Kumar Nayak, Konda Reddy Mopuri, Saksham Jain, Anirban Chakraborty, Mining Data Impressions from Deep Models as Substitute for the Unavailable Training Data, in IEEE Trans. on PAMI , 2021. [PDF] [Impact Factor: 16.4]
  3. N. Tsuchihashi, R. Wada, M. Osaki, T. Inoue, K. R. Mopuri, H. Bilen, T. Nishiyama, K. Fujita, K. Kusanagi. Early Stuck Pipe Sign Detection with Depth-Domain 3D Convolutional Neural Network Using Actual Drilling Data, SPE Journal (2021). [Impact Factor: 3.48, Scopus Rank: #4/189]
  4. Konda Reddy Mopuri*, Aditya Ganeshan*, and R. Venkatesh Babu, Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations, in IEEE Trans. on PAMI, 2018. [Impact Factor: 16.4] [~150 Google Scholar Citations]
  5. Konda Reddy Mopuri*, Utsav Garg, R. Venkatesh Babu, CNN Fixations: An unraveling approach to visualize the discriminative image regions, in IEEE Trans. on IP, 2018. [Impact Factor: 10.86]
  6. Srinivas S, Sarvadevabhatla R, Konda Reddy Mopuri, Prabhu N, Kruthiventi S and Radhakrishnan V, A taxonomy of Deep Convolutional Neural Networks for Computer Vision, in Frontiers in Robotics and AI, 2016. [200+ Google Scholar Citations]
Conferences
  1. Gaurav Patel, Konda Reddy Mopuri, and Qiang Qiu. "Learning to Retain while Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillation." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023.[ PDF ].
  2. Arun Kumar Sivapuram, Abhijit Pal, Konda Reddy Mopuri, Rama Krishna Gorthi, "Adv-Cut Paste: Semantic Adversarial Class Specific Data Augmentation Technique for Object Detection", ICPR-2022 (Accepted).
  3. Inoue, Tomoya, Nakagawa, Yujin, Wada, Ryota, Miyoshi, Keisuke, Abe, Shungo, Kuroda, Kouhei, Nishi, Masatoshi, Bilen, Hakan, and Konda Reddy Mopuri. ”Early Stuck Detection Using Supervised and Unsupervised Machine Learning Approaches”, Offshore Technology Conference Asia, Virtual and Kuala Lumpur, Malaysia, 2022.
  4. Yujin Nakagawa, Tomoya Inoue, Hakan Bilen, Konda Reddy Mopuri, Keisuke Miyoshi, Shungo Abe, Ryota Wada, Kouhei Kuroda, Hitoshi Tamamura, An Unsupervised Learning Model for Pipe Stuck Predictions Using a Long Short-Term Memory Autoencoder Architecture, SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, 2021.
  5. Yujin Nakagawa, Tomoya Inoue, Hakan Bilen, Konda Reddy Mopuri, Keisuke Miyoshi, Shungo Abe, Ryota Wada, Kouhei Kuroda, Masatoshi Nishi, Hiroyasu Ogasawara, Approach for Real-Time Prediction of Pipe Stuck Risk Using a Long Short-Term Memory Autoencoder Architecture, Abu Dhabi International Petroleum Exhibition and Conference, 2021.
  6. Harsh Rangwani, Konda Reddy Mopuri, R. Venkatesh Babu, Class Balancing GAN with a Classifier in the Loop, UAI, 2021. [CORE A]
  7. Bo Zhao, Konda Reddy Mopuri, Hakan Bilen, Dataset Condensation with Gradient Matching, ICLR, 2021 [CORE A*; Oral: < 2% of the submissions; 2nd top rated out of all submissions].
  8. Konda Reddy Mopuri*, Gaurav Kumar Nayak*,Anirban Chakraborty, Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation, WACV, 2021. [PDF] [CORE A]
  9. Konda Reddy Mopuri*, Vaisakh Shaj*, R. Venkatesh Babu, Adversarial Fooling Beyond Flipping the Label, AMLCV Workshop, CVPR, 2020. [CORE A*]
  10. Konda Reddy Mopuri*, Gaurav Kumar Nayak*, Vaisakh Shaj*, R. Venkatesh Babu, Anirban Chakraborty, Zero-Shot Knowledge Distillation in Deep Networks, ICML, 2019. [CORE A*; 125+ Google Scholar Citations]
  11. Konda Reddy Mopuri*, Phani Krishna Uppala*, and R. Venkatesh Babu, Ask, Acquire and Attack: Data-free UAP Generation using Class Impressions, ECCV, 2018. [CORE A*] [50+ Google Scholar Citations]
  12. Vivek B S, Konda Reddy Mopuri, and R. Venkatesh Babu, Gray-box Adversarial Training, ECCV, 2018. [CORE A*]
  13. Konda Reddy Mopuri*, Utkarsh Ojha*, Utsav Garg, and R. Venkatesh Babu, NAG: Network for Adversary Generation, CVPR, 2018. [CORE A*] [100+ Google Scholar Citations]
  14. Akshayvarun Subramanya, Konda Reddy Mopuri, and R. Venkatesh Babu, BatchOut: Batch-level feature augmentation to improve robustness to adversarial examples, ICVGIP 2018.
  15. Konda Reddy Mopuri, Vishal B. Athreya and R. Venkatesh Babu, Learning Representations with Strong Supervision for Image Search, Best Paper Award at SPCOM, 2018.
  16. Konda Reddy Mopuri*, Utsav Garg* and R. Venkatesh Babu, Fast Feature Fool: A data independent approach to universal adversarial perturbations, BMVC, 2017. [150+ Google Scholar Citations]
  17. Konda Reddy Mopuri and R. Venkatesh Babu, Towards Semantic Visual Representation: Augmenting Image Representation with Natural Language Descriptors, in ICVGIP, 2016.
  18. Konda Reddy Mopuri and R. Venkatesh Babu,Object Level Deep Feature Pooling for Compact Image Representation, in Deep Vision Workshop, CVPR, 2015. [CORE A*] [~75 Google Scholar Citations]
  19. Konda Reddy Mopuri, Jayasimha Talur, and R. Venkatesh Babu, Sparse coding based VLAD for efficient image retrieval, CONECCT, 2014.
  20. Konda Reddy Mopuri, Sahil Arora, and R. Venkatesh Babu. Spatio-temporal feature based vlad for efficient video retrieval, NCVPRIPG, 2013.