GR.

Computer vision · Deep learning

Portrait of Gani Rahmon

Gani
Rahmon.

Understanding motion.
Making sense of images.

I work on computer vision systems that detect, segment, and track objects—from moving objects in video to cells in microscopy and wildlife in infrared imagery.

Explore my research Google Scholar

01 / Research

Seeing beyond
the obvious.

Deep learning for challenging scenes, changing environments, and fine-grained visual detail.

01

Motion analysis &
object tracking

Multi-stream and multi-cue architectures that combine appearance, motion, and change information to segment moving objects despite clutter, illumination changes, camera motion, and occlusion.

Read DeepFTSG
02

Biomedical image
segmentation

Deep networks for cell and nuclei segmentation, including weak supervision and the challenges of transferring between simulated and real microscopy data.

Read the cell segmentation paper
03

Small-object detection
in infrared imagery

Detection and multi-object tracking in UAV imagery to improve temporal consistency, reduce false detections, and support bird counting in nighttime infrared video.

Read the wildlife study

02 / Publications

Research in print.

View Google Scholar

18 publications, preprints, and challenge reports · 2020–2026

  1. 2026

    International Journal of Computer Vision

    Domain Generalization for Multiple Video Object Segmentation and Tracking Using Transformers and Smart Memory

    E. S. Kazemi, I. E. Toubal, G. Rahmon, J. Collins, K. Palaniappan

  2. 2026

    IEEE Transactions on Medical Imaging

    BONBID-HIE 2023: Lesion Segmentation Challenge in BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy

    R. Bao, A. N. Foster, Y. Song, G. Rahmon, et al.

  3. 2025

    Wildlife Society Bulletin

    Assessing the Potential of Unoccupied Aerial Vehicles and Deep Learning to Survey Wild Turkey Populations

    A. R. Schumacher, I. E. Toubal, G. Rahmon, T. Krock, J. B. Hardin, K. Palaniappan, M. E. Byrne

  4. 2025

    IEEE Applied Imagery Pattern Recognition Workshop (AIPR)

    Visual Feature Tracking Algorithm for Veterinary Lameness Assessment in Horses

    K. Safavigerdini, T. Kucukpinar, G. Rahmon, et al.

  5. 2025

    IEEE/CVF ICCV Workshops

    The Third Visual Object Tracking Segmentation VOTS2025 Challenge Results

    M. Kristan, J. Matas, P. Tokmakov, et al., G. Rahmon, et al.

  6. 2025

    arXiv preprint · arXiv:2507.18921

    HQ-SMem: Video Segmentation and Tracking Using Memory Efficient Object Embedding With Selective Update and Self-Supervised Distillation Feedback

    E. S. Kazemi, I. E. Toubal, G. Rahmon, J. Collins, K. Palaniappan

  7. 2025

    SPIE · Geospatial Informatics XV

    Optimizing Short-Term Data Association for Multiple Object Tracking

    Y. Kuchimanchi, G. Rahmon, T. Banerjee, S. Sahni, G. Seetharaman, K. Palaniappan

  8. 2025

    Computer Vision – ECCV 2024 Workshops

    The Second Visual Object Tracking Segmentation VOTS2024 Challenge Results

    M. Kristan, J. Matas, P. Tokmakov, et al., G. Rahmon, et al.

  9. 2025

    AI for Brain Lesion Detection and Trauma Video Action Recognition

    Enhancing Lesion Segmentation in the BONBID-HIE Challenge: An Ensemble Strategy

    E. S. Kazemi, I. E. Toubal, G. Rahmon, et al.

  10. 2024

    Lecture Notes in Computer Science · BONBID-HIE Challenge Proceedings

    Fusion of Deep and Local Features Using Random Forests for Neonatal HIE Segmentation

    I. E. Toubal, E. S. Kazemi, G. Rahmon, et al.

  11. 2024

    Visual Object Tracking and Segmentation Challenge Report

    The Second Visual Object Tracking Segmentation VOTS2024 Challenge Results

    M. Kristan, J. Matas, P. Tokmakov, et al., G. Rahmon, et al.

  12. 2024

    International Journal of Computer Vision

    DeepFTSG: Multi-stream Asymmetric USE-Net Trellis Encoders with Shared Decoder Feature Fusion Architecture for Video Motion Segmentation

    G. Rahmon, K. Palaniappan, I. E. Toubal, F. Bunyak, R. Rao, G. Seetharaman

  13. 2023

    IEEE/CVF ICCV Workshops

    The First Visual Object Tracking Segmentation VOTS2023 Challenge Results

    M. Kristan, J. Matas, M. Danelljan, et al., G. Rahmon, et al.

  14. 2023
  15. 2023

    Nature Methods

    The Cell Tracking Challenge: 10 Years of Objective Benchmarking

    M. Maška, V. Ulman, P. Delgado-Rodriguez, G. Rahmon, et al.

  16. 2021
  17. 2021

    International Conference on Pattern Recognition

    Motion U-Net: Multi-cue Encoder-Decoder Network for Motion Segmentation

    G. Rahmon, F. Bunyak, G. Seetharaman, K. Palaniappan

  18. 2020

    IEEE Applied Imagery Pattern Recognition Workshop (AIPR)

    Evaluation of Different Decision Fusion Mechanisms for Robust Moving Object Detection

    G. Rahmon, F. Bunyak, G. Seetharaman, K. Palaniappan

03 / Academic appointments

Research & teaching.

August 2019 — May 2026

Graduate Research Assistant

University of Missouri · Columbia, MO

Advisor: Dr. K. Palaniappan

Developed deep learning methods for moving-object detection and segmentation, multi-object tracking, and biomedical image analysis.

August 2020 — May 2026

Graduate Teaching Assistant

University of Missouri · Columbia, MO

  • ECE 3210: Microprocessor Engineering for Electrical Engineers
  • CMP SC 2050: Algorithm Design and Programming II

Supported C++ and embedded-systems laboratories, prepared instructional materials, guided debugging, assessed assignments, and mentored new teaching assistants.

04 / Industry experience

Research meets
practical engineering.

Oct 2018 — Aug 2019

iOS / Android Mobile Developer

Alif Capital · Dushanbe, Tajikistan

Built and maintained features for alif.mobi, a digital payment platform supporting utility payments, wallet transfers, and card transactions. Refactored application code and wrote unit tests.

Sep 2017 — Mar 2018

Android Developer · Part-time

TMT Bilisim · Izmir, Turkey

Built a marine marketplace application from prototypes to responsive Android interfaces and backend API integration.

Jun 2015 — Jun 2017

Android Developer · Part-time

Mobilentis · Istanbul, Turkey

Developed Android applications including ForumBox, JetForMe, Cosalindo, MobiLeague, and STT, spanning interface design and backend integration.

Earlier experience

Aug — Sep 2014

Web & Mobile Intern

Emre Toraman Web Programming · Izmir, Turkey

Contributed to hybrid applications using HTML, CSS, JavaScript, and PhoneGap.

Aug — Sep 2013

IT Specialist Intern

Tcell · Dushanbe, Tajikistan

Assisted with mobile base-station diagnostics and explored telecommunications infrastructure.

05 / Contact

Let’s connect.