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Robust Surgical Robotic Instrument Tracking via Sequential Multi-Cue Fusion and Sim-to-Real Self-Training
Efficient and robust tracking of surgical robotic instruments is important for robot-assisted minimally invasive surgery, yet remains challenging due to the complexity of surgical scenes and the unconventional geometry of surgical instruments. Keypoint-based approaches are efficient, but their perfo
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