Anoop Cherian

Anoop Cherian
Anoop's Quick Links

  • Biography

    Anoop was a postdoctoral researcher in the LEAR group at Inria from 2012-2015 where his research was on the estimation and tracking of human poses in videos. From 2015-2017, he was a Research Fellow at the Australian National University, where he worked on the problem of recognizing human activities in video sequences. Anoop is the recipient of the Best Student Paper award at the Intl. Conference on Image Processing in 2012. Currently, his research focus is on modeling the semantics of video data.

  • Recent News & Events

    •  NEWS    MERL Researchers to Present 2 Conference and 11 Workshop Papers at NeurIPS 2024
      Date: December 10, 2024 - December 15, 2024
      Where: Advances in Neural Processing Systems (NeurIPS)
      MERL Contacts: Petros T. Boufounos; Matthew Brand; Ankush Chakrabarty; Anoop Cherian; François Germain; Toshiaki Koike-Akino; Christopher R. Laughman; Jonathan Le Roux; Jing Liu; Suhas Lohit; Tim K. Marks; Yoshiki Masuyama; Kieran Parsons; Kuan-Chuan Peng; Diego Romeres; Pu (Perry) Wang; Ye Wang; Gordon Wichern
      Research Areas: Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Human-Computer Interaction, Information Security
      Brief
      • MERL researchers will attend and present the following papers at the 2024 Advances in Neural Processing Systems (NeurIPS) Conference and Workshops.

        1. "RETR: Multi-View Radar Detection Transformer for Indoor Perception" by Ryoma Yataka (Mitsubishi Electric), Adriano Cardace (Bologna University), Perry Wang (Mitsubishi Electric Research Laboratories), Petros Boufounos (Mitsubishi Electric Research Laboratories), Ryuhei Takahashi (Mitsubishi Electric). Main Conference. https://neurips.cc/virtual/2024/poster/95530

        2. "Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads" by Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Joanna Matthiesen (Math Kangaroo USA), Kevin Smith (Massachusetts Institute of Technology), Josh Tenenbaum (Massachusetts Institute of Technology). Main Conference, Datasets and Benchmarks track. https://neurips.cc/virtual/2024/poster/97639

        3. "Probabilistic Forecasting for Building Energy Systems: Are Time-Series Foundation Models The Answer?" by Young-Jin Park (Massachusetts Institute of Technology), Jing Liu (Mitsubishi Electric Research Laboratories), François G Germain (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Gordon Wichern (Mitsubishi Electric Research Laboratories), Navid Azizan (Massachusetts Institute of Technology), Christopher R. Laughman (Mitsubishi Electric Research Laboratories), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories). Time Series in the Age of Large Models Workshop.

        4. "Forget to Flourish: Leveraging Model-Unlearning on Pretrained Language Models for Privacy Leakage" by Md Rafi Ur Rashid (Penn State University), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Shagufta Mehnaz (Penn State University), Ye Wang (Mitsubishi Electric Research Laboratories). Workshop on Red Teaming GenAI: What Can We Learn from Adversaries?

        5. "Spatially-Aware Losses for Enhanced Neural Acoustic Fields" by Christopher Ick (New York University), Gordon Wichern (Mitsubishi Electric Research Laboratories), Yoshiki Masuyama (Mitsubishi Electric Research Laboratories), François G Germain (Mitsubishi Electric Research Laboratories), Jonathan Le Roux (Mitsubishi Electric Research Laboratories). Audio Imagination Workshop.

        6. "FV-NeRV: Neural Compression for Free Viewpoint Videos" by Sorachi Kato (Osaka University), Takuya Fujihashi (Osaka University), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Takashi Watanabe (Osaka University). Machine Learning and Compression Workshop.

        7. "GPT Sonography: Hand Gesture Decoding from Forearm Ultrasound Images via VLM" by Keshav Bimbraw (Worcester Polytechnic Institute), Ye Wang (Mitsubishi Electric Research Laboratories), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories). AIM-FM: Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond Workshop.

        8. "Smoothed Embeddings for Robust Language Models" by Hase Ryo (Mitsubishi Electric), Md Rafi Ur Rashid (Penn State University), Ashley Lewis (Ohio State University), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Kieran Parsons (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories). Safe Generative AI Workshop.

        9. "Slaying the HyDRA: Parameter-Efficient Hyper Networks with Low-Displacement Rank Adaptation" by Xiangyu Chen (University of Kansas), Ye Wang (Mitsubishi Electric Research Laboratories), Matthew Brand (Mitsubishi Electric Research Laboratories), Pu Wang (Mitsubishi Electric Research Laboratories), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories). Workshop on Adaptive Foundation Models.

        10. "Preference-based Multi-Objective Bayesian Optimization with Gradients" by Joshua Hang Sai Ip (University of California Berkeley), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories), Ali Mesbah (University of California Berkeley), Diego Romeres (Mitsubishi Electric Research Laboratories). Workshop on Bayesian Decision-Making and Uncertainty. Lightning talk spotlight.

        11. "TR-BEACON: Shedding Light on Efficient Behavior Discovery in High-Dimensions with Trust-Region-based Bayesian Novelty Search" by Wei-Ting Tang (Ohio State University), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories), Joel A. Paulson (Ohio State University). Workshop on Bayesian Decision-Making and Uncertainty.

        12. "MEL-PETs Joint-Context Attack for the NeurIPS 2024 LLM Privacy Challenge Red Team Track" by Ye Wang (Mitsubishi Electric Research Laboratories), Tsunato Nakai (Mitsubishi Electric), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Kento Oonishi (Mitsubishi Electric), Takuya Higashi (Mitsubishi Electric). LLM Privacy Challenge. Special Award for Practical Attack.

        13. "MEL-PETs Defense for the NeurIPS 2024 LLM Privacy Challenge Blue Team Track" by Jing Liu (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Tsunato Nakai (Mitsubishi Electric), Kento Oonishi (Mitsubishi Electric), Takuya Higashi (Mitsubishi Electric). LLM Privacy Challenge. Won 3rd Place Award.

        MERL members also contributed to the organization of the Multimodal Algorithmic Reasoning (MAR) Workshop (https://marworkshop.github.io/neurips24/). Organizers: Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Honglu Zhou (Salesforce Research), Kevin Smith (Massachusetts Institute of Technology), Tim K. Marks (Mitsubishi Electric Research Laboratories), Juan Carlos Niebles (Salesforce AI Research), Petar Veličković (Google DeepMind).
    •  
    •  NEWS    MERL at the International Conference on Robotics and Automation (ICRA) 2024
      Date: May 13, 2024 - May 17, 2024
      Where: Yokohama, Japan
      MERL Contacts: Anoop Cherian; Radu Corcodel; Stefano Di Cairano; Chiori Hori; Siddarth Jain; Devesh K. Jha; Jonathan Le Roux; Diego Romeres; William S. Yerazunis
      Research Areas: Artificial Intelligence, Machine Learning, Optimization, Robotics, Speech & Audio
      Brief
      • MERL made significant contributions to both the organization and the technical program of the International Conference on Robotics and Automation (ICRA) 2024, which was held in Yokohama, Japan from May 13th to May 17th.

        MERL was a Bronze sponsor of the conference, and exhibited a live robotic demonstration, which attracted a large audience. The demonstration showcased an Autonomous Robotic Assembly technology executed on MELCO's Assista robot arm and was the collaborative effort of the Optimization and Robotics Team together with the Advanced Technology department at Mitsubishi Electric.

        MERL researchers from the Optimization and Robotics, Speech & Audio, and Control for Autonomy teams also presented 8 papers and 2 invited talks covering topics on robotic assembly, applications of LLMs to robotics, human robot interaction, safe and robust path planning for autonomous drones, transfer learning, perception and tactile sensing.
    •  

    See All News & Events for Anoop

  • Research Highlights

  • Internships with Anoop

    • CV0075: Internship - Multimodal Embodied AI

      MERL is looking for a self-motivated intern to work on problems at the intersection of multimodal large language models and embodied AI in dynamic indoor environments. The ideal candidate would be a PhD student with a strong background in machine learning and computer vision, as demonstrated by top-tier publications. The candidate must have prior experience in designing synthetic scenes (e.g., 3D games) using popular graphics software, embodied AI, large language models, reinforcement learning, and the use of simulators such as Habitat/SoundSpaces. Hands on experience in using animated 3D human shape models (e.g., SMPL and variants) is desired. The intern is expected to collaborate with researchers in computer vision at MERL to develop algorithms and prepare manuscripts for scientific publications.

      Required Specific Experience

      • Experience in designing 3D interactive scenes
      • Experience with vision based embodied AI using simulators (implementation on real robotic hardware would be a plus).
      • Experience training large language models on multimodal data
      • Experience with training reinforcement learning algorithms
      • Strong foundations in machine learning and programming
      • Strong track record of publications in top-tier computer vision and machine learning venues (such as CVPR, NeurIPS, etc.).

    • CV0100: Internship - Simulation for Human-Robot Interaction

      MERL is looking for a self-motivated intern to develop a simulation platform to train vision-and-language models for dynamic human-robot interaction. The ideal intern must have a strong background in computer graphics, computer vision, and machine learning, as well as experience in using the latest graphics simulation toolboxes and physics engines. Working knowledge of recent multimodal generative AI methods is desired. The intern is expected to collaborate with researchers in the computer vision team at MERL to develop algorithms and prepare manuscripts for scientific publications.

      Required Specific Experience

      • Experience in designing novel realistic 3D interactive scenes for robot learning
      • Experience with extending vision-based embodied AI simulators
      • Strong foundations in machine learning and programming
      • Foundations in optimization, specifically scheduling algorithms, would be a strong plus.
      • Strong track record of publications in top-tier computer vision and machine learning venues (such as CVPR, NeurIPS, etc.)
      • Must be enrolled in a graduate program, ideally towards a Ph.D.

    • CV0101: Internship - Multimodal Algorithmic Reasoning

      MERL is looking for a self-motivated intern to research on problems at the intersection of multimodal large language models and neural algorithmic reasoning. An ideal intern would be a Ph.D. student with a strong background in machine learning and computer vision. The candidate must have prior experience with training multimodal LLMs for solving vision-and-language tasks. Experience in participating and winning mathematical Olympiads is desired. Publications in theoretical machine learning venues would be a strong plus. The intern is expected to collaborate with researchers in the computer vision team at MERL to develop algorithms and prepare manuscripts for scientific publications.

      Required Specific Experience

      • Experience with training large vision-and-language models
      • Experience with solving mathematical reasoning problems
      • Experience with programming in Python using PyTorch
      • Enrolled in a PhD program
      • Strong track record of publications in top-tier computer vision and machine learning venues (such as CVPR, NeurIPS, etc.).

    See All Internships at MERL

  • MERL Publications

    •  Cherian, A., Peng, K.-C., Lohit, S., Matthiesen, J., Smith, K., Tenenbaum, J.B., "Evaluating Large Vision-and-Language Models on Children’s Mathematical Olympiads", Advances in Neural Information Processing Systems (NeurIPS), November 2024.
      BibTeX TR2024-160 PDF Presentation
      • @inproceedings{Cherian2024nov,
      • author = {{Cherian, Anoop and Peng, Kuan-Chuan and Lohit, Suhas and Matthiesen, Joanna and Smith, Kevin and Tenenbaum, Joshua B.}},
      • title = {Evaluating Large Vision-and-Language Models on Children’s Mathematical Olympiads},
      • booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
      • year = 2024,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2024-160}
      • }
    •  Yin, J., Luo, A., Du, Y., Cherian, A., Marks, T.K., Le Roux, J., Gan, C., "Disentangled Acoustic Fields For Multimodal Physical Scene Understanding", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2024.
      BibTeX TR2024-125 PDF
      • @inproceedings{Yin2024sep,
      • author = {Yin, Jie and Luo, Andrew and Du, Yilun and Cherian, Anoop and Marks, Tim K. and Le Roux, Jonathan and Gan, Chuang}},
      • title = {Disentangled Acoustic Fields For Multimodal Physical Scene Understanding},
      • booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
      • year = 2024,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2024-125}
      • }
    •  Cherian, A., Jain, S., Marks, T.K., "Few-shot Transparent Instance Segmentation for Bin Picking", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2024.
      BibTeX TR2024-127 PDF
      • @inproceedings{Cherian2024sep,
      • author = {Cherian, Anoop and Jain, Siddarth and Marks, Tim K.}},
      • title = {Few-shot Transparent Instance Segmentation for Bin Picking},
      • booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
      • year = 2024,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2024-127}
      • }
    •  Zhang, J., Zhang, F., Rodriguez, C., Ben-Shabat, I., Cherian, A., Gould, S., "Temporally Grounding Instructional Diagrams in Unconstrained Videos", arXiv, July 2024.
      BibTeX arXiv
      • @article{Zhang2024jul4,
      • author = {Zhang, Jiahao and Zhang, Frederic and Rodriguez, Cristian and Ben-Shabat, Itzik and Cherian, Anoop and Gould, Stephen}},
      • title = {Temporally Grounding Instructional Diagrams in Unconstrained Videos},
      • journal = {arXiv},
      • year = 2024,
      • month = jul,
      • url = {https://arxiv.org/abs/2407.12066}
      • }
    •  Ni, H., Egger, B., Lohit, S., Cherian, A., Wang, Y., Koike-Akino, T., Huang, S.X., Marks, T.K., "TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2024, pp. 9015-9025.
      BibTeX TR2024-059 PDF Video Software Presentation
      • @inproceedings{Ni2024jun,
      • author = {Ni, Haomiao and Egger, Bernhard and Lohit, Suhas and Cherian, Anoop and Wang, Ye and Koike-Akino, Toshiaki and Huang, Sharon X. and Marks, Tim K.},
      • title = {TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models},
      • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2024,
      • pages = {9015--9025},
      • month = jun,
      • url = {https://www.merl.com/publications/TR2024-059}
      • }
    See All MERL Publications for Anoop

  • Other Publications

    •  Anoop Cherian and Stephen Gould, "Second-order Temporal Pooling for Action Recognition", International Journal of Computer Vision (IJCV), 2018.
      BibTeX
      • @Article{cherian2018ijcv,
      • author = {Cherian, Anoop and Gould, Stephen},
      • title = {Second-order Temporal Pooling for Action Recognition},
      • journal = {International Journal of Computer Vision (IJCV)},
      • year = 2018,
      • publisher = {Springer}
      • }
    •  Rodrigo Santa Cruz, Basura Fernando, Anoop Cherian and Stephen Gould, "Visual Permutation Learning", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.
      BibTeX
      • @Article{cherian2018permutation,
      • author = {Santa Cruz, Rodrigo and Fernando, Basura and Cherian, Anoop and Gould, Stephen},
      • title = {Visual Permutation Learning},
      • journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
      • year = 2018,
      • publisher = {IEEE}
      • }
    •  Jue Wang, Anoop Cherian, Fatih Porikli and Stephen Gould, "Video Representation Learning Using Discriminative Pooling", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
      BibTeX
      • @Inproceedings{cherian_representation_cvpr18,
      • author = {Wang, Jue and Cherian, Anoop and Porikli, Fatih and Gould, Stephen},
      • title = {Video Representation Learning Using Discriminative Pooling},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2018
      • }
    •  Suryansh Kumar, Anoop Cherian, Yuchao Dai and Hongdong Li, "Scalable Dense Non-rigid Structure-from-Motion: A Grassmannian Perspective", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
      BibTeX
      • @Inproceedings{cherian_rigid_cvpr18,
      • author = {Kumar, Suryansh and Cherian, Anoop and Dai, Yuchao and Li, Hongdong},
      • title = {Scalable Dense Non-rigid Structure-from-Motion: A Grassmannian Perspective},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2018
      • }
    •  Anoop Cherian, Suvrit Sra, Stephen Gould and Richard Hartley, "Non-Linear Temporal Subspace Representations for Activity Recognition", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
      BibTeX
      • @Inproceedings{cherian_temporal_cvpr18,
      • author = {Cherian, Anoop and Sra, Suvrit and Gould, Stephen and Hartley, Richard},
      • title = {Non-Linear Temporal Subspace Representations for Activity Recognition},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2018
      • }
    •  Anoop Cherian, Basura Fernando, Mehrtash Harandi and Stephen Gould, "Generalized Rank Pooling for Activity Recognition", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
      BibTeX
      • @Inproceedings{cherian2017generalized,
      • author = {Cherian, Anoop and Fernando, Basura and Harandi, Mehrtash and Gould, Stephen},
      • title = {Generalized Rank Pooling for Activity Recognition},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2017
      • }
    •  Anoop Cherian, Panagiotis Stanitsas, Mehrtash Harandi, Vassilios Morellas and Nikolaos Papanikolopoulos, "Learning Discriminative Alpha-Beta Divergences for Positive Definite Matrices", International Conference on Computer Vision (ICCV), 2017.
      BibTeX
      • @Inproceedings{cherian_rigid_iccv17,
      • author = {Cherian, Anoop and Stanitsas, Panagiotis and Harandi, Mehrtash and Morellas, Vassilios and Papanikolopoulos, Nikolaos},
      • title = {Learning Discriminative Alpha-Beta Divergences for Positive Definite Matrices},
      • booktitle = {International Conference on Computer Vision (ICCV)},
      • year = 2017
      • }
    •  Rodrigo Santa Cruz, Basura Fernando, Anoop Cherian and Stephen Gould, "DeepPermNet: Visual Permutation Learning", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
      BibTeX
      • @Inproceedings{cruz2017deeppermnet,
      • author = {Cruz, Rodrigo Santa and Fernando, Basura and Cherian, Anoop and Gould, Stephen},
      • title = {DeepPermNet: Visual Permutation Learning},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2017
      • }
    •  Anoop Cherian, Vassilios Morellas and Nikolaos Papanikolopoulos, "Bayesian Non-Parametric clustering for positive definite matrices", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
      BibTeX
      • @Article{cherian2016bayesian,
      • author = {Cherian, Anoop and Morellas, Vassilios and Papanikolopoulos, Nikolaos},
      • title = {Bayesian Non-Parametric clustering for positive definite matrices},
      • journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
      • year = 2016,
      • publisher = {IEEE}
      • }
    •  Piotr Koniusz and Anoop Cherian, "Sparse coding for third-order super-symmetric tensor descriptors with application to texture recognition", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
      BibTeX
      • @Inproceedings{koniusz2016sparse,
      • author = {Koniusz, Piotr and Cherian, Anoop},
      • title = {Sparse coding for third-order super-symmetric tensor descriptors with application to texture recognition},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2016
      • }
    •  Piotr Koniusz, Anoop Cherian and Fatih Porikli, "Tensor representations via kernel linearization for action recognition from 3D skeletons", European Conference on Computer Vision (ECCV), 2016.
      BibTeX
      • @Inproceedings{koniusz2016tensor,
      • author = {Koniusz, Piotr and Cherian, Anoop and Porikli, Fatih},
      • title = {Tensor representations via kernel linearization for action recognition from 3D skeletons},
      • booktitle = {European Conference on Computer Vision (ECCV)},
      • year = 2016,
      • organization = {Springer}
      • }
    •  Anoop Cherian, Julien Mairal, Karteek Alahari and Cordelia Schmid, "Mixing body-part sequences for human pose estimation", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.
      BibTeX
      • @Inproceedings{cherian2014mixing,
      • author = {Cherian, Anoop and Mairal, Julien and Alahari, Karteek and Schmid, Cordelia},
      • title = {Mixing body-part sequences for human pose estimation},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2014
      • }
    •  Anoop Cherian, "Nearest neighbors using compact sparse codes", International Conference on Machine Learning (ICML), 2014.
      BibTeX
      • @Inproceedings{cherian2014nearest,
      • author = {Cherian, Anoop},
      • title = {Nearest neighbors using compact sparse codes},
      • booktitle = {International Conference on Machine Learning (ICML)},
      • year = 2014
      • }
    •  Anoop Cherian and Suvrit Sra, "Riemannian sparse coding for positive definite matrices", European Conference on Computer Vision (ECCV), 2014.
      BibTeX
      • @Inproceedings{cherian2014riemannian,
      • author = {Cherian, Anoop and Sra, Suvrit},
      • title = {Riemannian sparse coding for positive definite matrices},
      • booktitle = {European Conference on Computer Vision (ECCV)},
      • year = 2014,
      • organization = {Springer}
      • }
    •  Anoop Cherian, Suvrit Sra, Arindam Banerjee and Nikolaos Papanikolopoulos, "Jensen-Bregman logdet divergence with application to efficient similarity search for covariance matrices", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2013.
      BibTeX
      • @Article{cherian2013jensen,
      • author = {Cherian, Anoop and Sra, Suvrit and Banerjee, Arindam and Papanikolopoulos, Nikolaos},
      • title = {Jensen-Bregman logdet divergence with application to efficient similarity search for covariance matrices},
      • journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
      • year = 2013,
      • publisher = {IEEE}
      • }
    •  Anoop Cherian, Vassilios Morellas, Nikolaos Papanikolopoulos and Saad J Bedros, "Dirichlet process mixture models on symmetric positive definite matrices for appearance clustering in video surveillance applications", Computer Vision and Pattern Recognition (CVPR), 2011.
      BibTeX
      • @Inproceedings{cherian2011dirichlet,
      • author = {Cherian, Anoop and Morellas, Vassilios and Papanikolopoulos, Nikolaos and Bedros, Saad J},
      • title = {Dirichlet process mixture models on symmetric positive definite matrices for appearance clustering in video surveillance applications},
      • booktitle = {Computer Vision and Pattern Recognition (CVPR)},
      • year = 2011
      • }
    •  Anoop Cherian, Suvrit Sra, Arindam Banerjee and Nikolaos Papanikolopoulos, "Efficient similarity search for covariance matrices via the Jensen-Bregman LogDet divergence", International Conference on Computer Vision (ICCV), 2011.
      BibTeX
      • @Inproceedings{cherian2011efficient,
      • author = {Cherian, Anoop and Sra, Suvrit and Banerjee, Arindam and Papanikolopoulos, Nikolaos},
      • title = {Efficient similarity search for covariance matrices via the Jensen-Bregman LogDet divergence},
      • booktitle = {International Conference on Computer Vision (ICCV)},
      • year = 2011
      • }
    •  Suvrit Sra and Anoop Cherian, "Generalized dictionary learning for symmetric positive definite matrices with application to nearest neighbor retrieval", Machine Learning and Knowledge Discovery in Databases (ECML), 2011.
      BibTeX
      • @Article{sra2011generalized,
      • author = {Sra, Suvrit and Cherian, Anoop},
      • title = {Generalized dictionary learning for symmetric positive definite matrices with application to nearest neighbor retrieval},
      • journal = {Machine Learning and Knowledge Discovery in Databases (ECML)},
      • year = 2011
      • }
    •  Anoop Cherian, Vassilios Morellas and Nikolaos Papanikolopoulos, "Accurate 3D ground plane estimation from a single image", International Conference on Robotics and Automation, 2009.
      BibTeX
      • @Inproceedings{cherian2009accurate,
      • author = {Cherian, Anoop and Morellas, Vassilios and Papanikolopoulos, Nikolaos},
      • title = {Accurate 3D ground plane estimation from a single image},
      • booktitle = {International Conference on Robotics and Automation},
      • year = 2009
      • }

  • Software & Data Downloads

  • Videos

  • MERL Issued Patents

    • Title: "A Method and System for Scene-Aware Audio-Video Representation"
      Inventors: Cherian, Anoop; Chatterjee, Moitreya; Le Roux, Jonathan
      Patent No.: 12,056,213
      Issue Date: Aug 6, 2024
    • Title: "Artificial Intelligence System for Classification of Data Based on Contrastive Learning"
      Inventors: Cherian, Anoop; Aeron, Shuchin
      Patent No.: 11,809,988
      Issue Date: Nov 7, 2023
    • Title: "System and Method for Manipulating Two-Dimensional (2D) Images of Three-Dimensional (3D) Objects"
      Inventors: Marks, Tim; Medin, Safa; Cherian, Anoop; Wang, Ye
      Patent No.: 11,663,798
      Issue Date: May 30, 2023
    • Title: "InSeGAN: A Generative Approach to Instance Segmentation in Depth Images"
      Inventors: Cherian, Anoop; Pais, Goncalo; Marks, Tim; Sullivan, Alan
      Patent No.: 11,651,497
      Issue Date: May 16, 2023
    • Title: "Method and System for Scene-Aware Interaction"
      Inventors: Hori, Chiori; Cherian, Anoop; Chen, Siheng; Marks, Tim; Le Roux, Jonathan; Hori, Takaaki; Harsham, Bret A.; Vetro, Anthony; Sullivan, Alan
      Patent No.: 11,635,299
      Issue Date: Apr 25, 2023
    • Title: "Scene-Aware Video Encoder System and Method"
      Inventors: Cherian, Anoop; Hori, Chiori; Le Roux, Jonathan; Marks, Tim; Sullivan, Alan
      Patent No.: 11,582,485
      Issue Date: Feb 14, 2023
    • Title: "Low-latency Captioning System"
      Inventors: Hori, Chiori; Hori, Takaaki; Cherian, Anoop; Marks, Tim; Le Roux, Jonathan
      Patent No.: 11,445,267
      Issue Date: Sep 13, 2022
    • Title: "Anomaly Detector for Detecting Anomaly using Complementary Classifiers"
      Inventors: Cherian, Anoop; Wang, Jue
      Patent No.: 11,423,698
      Issue Date: Aug 23, 2022
    • Title: "System and Method for a Dialogue Response Generation System"
      Inventors: Hori, Chiori; Cherian, Anoop; Marks, Tim; Hori, Takaaki
      Patent No.: 11,264,009
      Issue Date: Mar 1, 2022
    • Title: "Scene-Aware Video Dialog"
      Inventors: Geng, Shijie; Gao, Peng; Cherian, Anoop; Hori, Chiori; Le Roux, Jonathan
      Patent No.: 11,210,523
      Issue Date: Dec 28, 2021
    See All Patents for MERL