Detection of loop closure in SLAM: A DeconvNet based approach A Mukherjee, S Chakraborty, SK Saha Applied Soft Computing 80, 650-656, 2019 | 14 | 2019 |
Learning deep representation for place recognition in slam A Mukherjee, S Chakraborty, SK Saha Pattern Recognition and Machine Intelligence: 7th International Conference …, 2017 | 7 | 2017 |
Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark K Lee, H Yang, S Chakraborty, Z Cai, G Swaminathan, A Ravichandran, ... Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 3 | 2022 |
A more abstractive summarization model S Chakraborty, X Li, S Chakraborty arXiv preprint arXiv:2002.10959, 2020 | 2 | 2020 |
Detecting cars in aerial photographs with a hierarchy of deconvolution nets S Chakraborty, D Maturana, S Scherer Technical Report CMU-RI-TR-16-60, Robotics Institute, Carnegie Mellon University, 2016 | 2 | 2016 |
Making compatible two robotic middlewares: ros and jderobot S Chakraborty, JM Canas Proceedings of the XVII Workshop on Physical Agents (WAF-2016), 147-154, 2016 | 2 | 2016 |
Learning to track object position through occlusion S Chakraborty, M Hebert arXiv preprint arXiv:2106.10766, 2021 | 1 | 2021 |
Liminating Intra-Class Variance in Classification Neural Networks with Adversarial Losses SC Mynepalli, S Chakraborty, R Madhok Carnegie Mellon University, 0 | 1 | |
Learning to detect occluded objects in videos S Chakraborty, M Hebert Carnegie Mellon University Pittsburgh, 2019 | | 2019 |
Multi-Goal Reinforcement Learning with Conditional Variational Autoencoders M Sieb, H Muthakana, S Chakraborty | | |
Publication Submission Form S Chakraborty, D Maturana, S Scherer | | |