Computer Vision in Low Light Scenes - Honda Research Institute USA

Computer Vision in Low Light Scenes

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Computer Vision in Low Light Scenes

Job Number: P23INT-43
This internship concerns with developing Vision based Mapping and Localization Algorithms for Autonomous Driving with focus on low light scenes with HDR Cameras. The candidate is responsible for developing deep learning models for low light HDR image enhancement and light invariant point features. This position offers a unique opportunity to contribute to the development of next-generation mapping technologies that operate effectively in challenging lighting conditions.
San Jose, CA

 

Key Responsibilities

  • Design and development of Deep Learning Models for low light HDR image enhancement and light invariant point features.
  • Integrate these models into our large-scale Mapping & Localization system.
  • Create and maintain datasets for training the network.
  • Develop evaluation metrics to confirm the efficacy of proposed algorithms.

 

 

Minimum Qualifications

  • Ph.D. or M.S student in Computer Science, Robotics, or related field.
  • Familiarity with Learning based and Classical Image Enhancement and Denoising Algorithms.
  • Familiarity with SOTA Vision and Deep Learning methods for estimating light invariant point features.
  • Ability to transfer conceptual models and ideas to working code in Python and/or C++.
  • Experience with Deep Learning frameworks PyTorch and/or TensorFlow

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Bonus Qualifications

  • Hands on experience with Vision based Mapping and Localization systems.
  • Publication record in top venues including CVPR, ICCV, ICRA, IROS, ECCV, NeurIPS, ICLR, etc.
  • Hands on experience with Deep Learning model optimization techniques and real-time algorithms for edge devices

 

Desired Start Date 01/06/2025 

 

Duration

 

3 Months

 

Alternate Way to Apply

Send an e-mail to careers@honda-ri.com with the following:
- Subject line including the job number(s) you are applying for 
- Recent CV 
- A cover letter highlighting relevant background (Optional)

Please, do not contact our office to inquiry about your application status.