Key Responsibilities:
- Participate in research of advanced intelligent video processing algorithms using state-of-the-art recognition technologies for multimedia and communication applications
- Research in intelligent video processing, computer vision, pattern recognition or machine learning for applications like object detection/tracking, event recognition, video analysis, etc.
- Perform research into leading edge and emerging video technologies, ideas, approaches and keep up to date with new video processing standards and general industry trends
- C-model simulation for video processing algorithm development and verification.
Required Qualifications:
- PhD in Computer Science, Robotics, Electrical Engineering, or related field with a focus on computer graphic, computer vision or robotics perception.
- Insightful know-how on deep-learning, CNN/transformer, traditional machine learning and recognition technologies, such as human and object feature extractions, visual tracking, event recognition
- PC-based algorithmic intelligent video processing algorithm development for machine vision projects and applications.
- Implementation of low-level vision algorithms on embedded DSP platforms with associated CPU and memory bandwidth limitations
- Working knowledge of C/C++ and/or Matlab and proficiency with DSP and filter design.
- Familiarity with ASIC design approach and environment Familiar with OpenCV library and related algorithms
- Ability to express ideas and communicate effectively.
- Insightful understanding of compact CNN model and design, such as ShuffleNet, MobileNet, SqueezeNet, etc.
- Be familiar with model compression algorithms on video processing, such as knowledge distillation, parameter pruning and sharing, low-rank factorization, etc.
- Rich experiences in handling the deep learning development tools, such as Pytorch, TensorFlow, etc.
- Any of the following skills and experiences would be an added advantage:
- Key image processing algorithms such as super resolution/HDR/contrast enhancement for display devices.
- Publications on top-ranking conferences and journals in related fields, such as CVPR, ICCV, NIPS, TPAMI, etc.
- Top-ranking and/or award receivers in world competition in video processing field
- Research experience on large cv/language model
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