HighlightNet: Highlighting Low-Light Potential Features for Real-Time UAV Tracking

Understand

Low-light environments have posed a formidable challenge for robust unmanned aerial vehicle (UAV) tracking even with state-of-the-art (SOTA) trackers since the potential image features are hard to extract under adverse light conditions.

• Besides, due to the low visibility, accurate online selection of the object also becomes extremely difficult for human monitors to initialize UAV tracking in ground control stations.
• To solve these problems, this work proposes a novel enhancer, i.e., HighlightNet, to light up potential objects for both human operators and UAV trackers.
• By employing Transformer, HighlightNet can adjust enhancement parameters according to global features and is thus adaptive for the illumination variation.