CV0332: Internship - 3D object detection and recognition MERL is looking for a self-motivated intern to work on 3D object detection and recognition using computer vision. The relevant topics in the scope include (but not limited to): monocular/multi-view/aerial 3D object detection, 3D object detection with large foundation models, open-vocabulary or auto-vocabulary 3D object detection and recognition, domain adaptation or generalization in 3D object detection, data-efficient methods for 3D object detection, small 3D object detection, etc. The candidates with experiences of 3D object detection are strongly preferred. The ideal candidate would be a PhD student with a strong background in computer vision and machine learning, and the candidate is expected to have published at least one paper in a top-tier computer vision, machine learning, or artificial intelligence venues, such as CVPR, ECCV, ICCV, ICML, ICLR, NeurIPS, AAAI, etc. Proficiency in Python programming and familiarity in at least one deep learning framework are necessary. The ideal candidate is required to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. The duration of the internship is ideally to be at least 3 months with a flexible start date. Required Specific Experience Experience with Python, PyTorch, and 3D object detection datasets (e.g. ScanNet, WildDet3D-Data, etc.). The pay range for this internship position will be 6-8K per month.

Research Areas:

Artificial Intelligence, Computer Vision, Machine Learning

Host:

Kuan-Chuan Peng

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