To start research in computer vision, choose a specific problem area, such as object detection, semantic segmentation, or 3D vision. Study recent literature on platforms like arXiv or CVF Open Access to identify research gaps.
Implement existing algorithms using frameworks like TensorFlow or PyTorch to understand state-of-the-art techniques. Conduct experiments using benchmark datasets like COCO or Cityscapes, and analyze results to identify areas for improvement.
Collaborate with academic mentors or join a research lab for guidance and resources. Publish your findings in computer vision conferences like CVPR or ICCV to establish your presence in the field.