[Computer Vision] Domain Adaptation and Video Style Transfer - HRI-US
[Computer Vision] Domain Adaptation and Video Style Transfer
This position investigates how to use domain adaptation and video style transfer to adapt driving scenes from a simulated environment to photo-realistic videos and analyze human perception for the synthesized video for user studies. You are expected to:
- Implement state-of-the-art domain adaptation and video style transfer algorithms.
- Evaluate the performance of the algorithms based on human perception.
- Analyze the impact in transfer-learning for driving-related tasks.
- M.S. or Ph.D. candidate in computer science or related STEM field.
- Familiarity and research experience in domain adaptation and style transfer.
- Highly proficient in software engineering using C++ and/or Python.
- Experience with deep learning software like TensorFlow or PyTorch.
- Experience in behavioral research and human-computer interaction.
- Familiarity with working on driving datasets.
Duration: 3 months