Visual representation of how Cell-TRACTR uses track queries to track cells and detect divisions.

Similar Items

• Cell-TRACTR detects cells in the first frame at time t 0. Object queries predicted to be a “cell” are converted to track queries. For Track Group Denoising (TGD), random noise is added to the track queries to get noised track queries. For Query Denoising (QD), random noise is added to the ground truth bounding boxes to generate noised track queries. All queries are processed together by the decoder. Attention masks are used to prevent information leakage between the object and track queries, the noised track queries generated from TGD, and the noised track queries generated from QD. The gray boxes indicate information being blocked between sets of queries while colored boxes indicate the flow of information.
  by: Owen M. O’Connor (11965460)
  Published: (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.
  by: Owen M. O’Connor (11965460)
  Published: (2025)
• Cells are initially detected in frame t₀ and then tracked to frame t₁. Object queries are processed in the first layer of the decoder for object detection. In the subsequent decoder layers, track queries are concatenated with the object queries to perform tracking.
  by: Owen M. O’Connor (11965460)
  Published: (2025)
• Time-lapse microscopy movie from the bacterial mother machine test set processed by Cell-TRACTR and evaluated with the Cell Tracking Challenge (CTC) OP_CTB metrics.
  by: Owen M. O’Connor (11965460)
  Published: (2025)
• Results from Cell-TRACTR and model overview for object detection.
  by: Owen M. O’Connor (11965460)
  Published: (2025)