Ajinkya Khoche

Lindstedtsvägen 24

Stockholm, Sweden

I’m a PhD candidate at the division of Robotics Perception and Learning at KTH, supervised by Prof. Patric Jensfelt and Dr. Sina Sharif Mansouri. My thesis focuses on long-range perception for autonomous trucking. My work is part of the ProSense project, supported by Vinnova.

During my PhD thesis, I have explored topics in scene perception, including object detection, segmentation and scene flow. I am also interested in 3D forecasting, scene rendering and world models. I am passionate about developing deployable and scalable methods that are robust to adverse weather and long-tail. I have experience in working with various sensors like LiDAR, cameras, and radar.

Previously, I graduated with M.Sc. in Systems, Controls and Robotics from KTH. My M.Sc. thesis explored depth estimation supervised using dense correspondences between image and SLAM-processed LiDAR under supervision of Dr. Mentar Mahmoudi at Audi Electronic Ventures, Ingolstad. I also hold B.Tech. + M.Tech, in Mechanical Engineering from Indian Institute of Technology, Kharagpur.

news

Oct 13, 2025	I’ll be presenting BlendCLIP: Bridging Synthetic and Real Domains for Zero-Shot 3D Object Classification with Multimodal Pretraining as an extended abstract at the 5th Workshop on Open-World 3D Scene Understanding with Foundation Models (OpenSUN3D). Come visit Hall II, Board #155 (19th Oct 15:00–16:00). Stay tuned for code release.
Aug 21, 2025	Our paper HiMo: High-Speed Objects Motion Compensation in Point Clouds is accepted to Transactions on Robotics (T-RO) journal. Stay tuned for dataset release!
Jan 31, 2025	Our paper SSF: Sparse Long-Range Scene Flow for Autonomous Driving is accepted to ICRA 2025. Source code is released here. See you in Atlanta!
Jun 02, 2024	Reporting from beautiful Jeju in South Korea. I’m here to present our paper Towards long-range 3d object detection for autonomous vehicles, accepted in IV 2024. Later during the month I’ll be at ECC 2024 in Stockholm to present another accepted paper Addressing Data Annotation Challenges in Multiple Sensors: A Solution for Scania Collected Datasets
Jun 06, 2022	Semantic 3d grid maps for autonomous driving is accepted to ITSC 2022!

selected publications

WACV 2026

BlendCLIP: Bridging Synthetic and Real Domains for Zero-Shot 3D Object Classification with Multimodal Pretraining

Ajinkya Khoche, Gergő László Nagy, Maciej Wozniak, and 2 more authors

arXiv preprint arXiv:2510.18244, 2026

arXiv Bib Video Code

@article{khoche2025blendclip,
  title = {BlendCLIP: Bridging Synthetic and Real Domains for Zero-Shot 3D Object Classification with Multimodal Pretraining},
  author = {Khoche, Ajinkya and L{\'a}szl{\'o} Nagy, Gerg{\H{o}} and Wozniak, Maciej and Gustafsson, Thomas and Jensfelt, Patric},
  journal = {arXiv preprint arXiv:2510.18244},
  year = {2026},
}

Under Review

DoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance

Ajinkya Khoche, Qingwen Zhang, Yixi Cai, and 2 more authors

arXiv preprint arXiv:2508.18506, 2025

arXiv Bib Video Code Website

@article{khoche2025dogflow,
  title = {DoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance},
  author = {Khoche, Ajinkya and Zhang, Qingwen and Cai, Yixi and Mansouri, Sina Sharif and Jensfelt, Patric},
  journal = {arXiv preprint arXiv:2508.18506},
  year = {2025},
}

T-RO 2025

HiMo: High-Speed Objects Motion Compensation in Point Clouds

Qingwen Zhang, Ajinkya Khoche, Yi Yang, and 4 more authors

IEEE Transactions on Robotics, 2025

arXiv Bib Video Code Website

@article{zhang2025himo,
  title = {HiMo: High-Speed Objects Motion Compensation in Point Clouds},
  author = {Zhang, Qingwen and Khoche, Ajinkya and Yang, Yi and Ling, Li and Mansouri, Sina Sharif and Andersson, Olov and Jensfelt, Patric},
  journal = {IEEE Transactions on Robotics},
  year = {2025},
}

ICRA 2025

SSF: Sparse Long-Range Scene Flow for Autonomous Driving

Ajinkya Khoche, Qingwen Zhang, Laura Pereira Sanchez, and 3 more authors

2025

arXiv Bib Video Code

@article{khoche2025ssf,
  title = {SSF: Sparse Long-Range Scene Flow for Autonomous Driving},
  author = {Khoche, Ajinkya and Zhang, Qingwen and Sanchez, Laura Pereira and Asefaw, Aron and Mansouri, Sina Sharif and Jensfelt, Patric},
  booktitle = {2025 IEEE International Conference on Robotics and Automation (ICRA)},
  year = {2025},
  keywords = {Point cloud compression;Measurement;Three-dimensional displays;Codes;Convolution;Scalability;Pipelines;Estimation;Feature extraction;Robotics and automation},
  doi = {10.1109/ICRA55743.2025.11128770},
}

M.Sc. Thesis

Depth Estimation from Images using Dense Camera-Lidar Correspondences and Deep Learning

Ajinkya Khoche

KTH, School of Electrical Engineering and Computer Science (EECS), 2020

Bib PDF

@mastersthesis{Khoche1417257,
  author = {Khoche, Ajinkya},
  institution = {KTH, School of Electrical Engineering and Computer Science (EECS)},
  school = {KTH, School of Electrical Engineering and Computer Science (EECS)},
  title = {Depth Estimation from Images using Dense Camera-Lidar Correspondences and Deep Learning},
  series = {TRITA-EECS-EX},
  number = {2020:12},
  year = {2020},
}