(11965460), O. M. O., & (463579), M. J. D. (2025). Example illustrating how object and track queries interact using an attention map processed by Cell-TRACTR across two subsequent frames. The schematic displays the actual output alongside the output the from top matching object queries. Extracted from the self-attention mechanism in the decoder, the attention map highlights the strength of interactions among the queries. Lighter colors indicate stronger interactions. The track queries tend to focus on themselves, while the object queries attend to the track query that corresponds most closely in location.
Chicago Style (17th ed.) Citation(11965460), Owen M. O’Connor, and Mary J. Dunlop (463579). Example Illustrating How Object and Track Queries Interact Using an Attention Map Processed by Cell-TRACTR Across Two Subsequent Frames. The Schematic Displays the Actual Output Alongside the Output the from Top Matching Object Queries. Extracted from the Self-attention Mechanism in the Decoder, the Attention Map Highlights the Strength of Interactions Among the Queries. Lighter Colors Indicate Stronger Interactions. The Track Queries Tend to Focus on Themselves, While the Object Queries Attend to the Track Query That Corresponds Most Closely in Location. 2025.
MLA (9th ed.) Citation(11965460), Owen M. O’Connor, and Mary J. Dunlop (463579). Example Illustrating How Object and Track Queries Interact Using an Attention Map Processed by Cell-TRACTR Across Two Subsequent Frames. The Schematic Displays the Actual Output Alongside the Output the from Top Matching Object Queries. Extracted from the Self-attention Mechanism in the Decoder, the Attention Map Highlights the Strength of Interactions Among the Queries. Lighter Colors Indicate Stronger Interactions. The Track Queries Tend to Focus on Themselves, While the Object Queries Attend to the Track Query That Corresponds Most Closely in Location. 2025.