The classes on the horizontal axis are sorted based on the performance of the task model without DTL. Dashed line shows the median performance of all classes. The implementation for MSTCN [2] and ASFormer [6] are from existing opensource code provided by corresponding authors. The result is shown in Fig.A1 and Fig.A2. Weanticipatemoreperformance improvement with more general constraints that go beyond knowledge in the annotations in future works.

The table below shows the notations grouped by the modules. This work was done when Ziwei Xu was visiting the Center for Research in Computer Vision. The classes on the horizontal axis are sorted based on the performance of the task model without DTL. Dashed line shows the median performance of all classes. The annotation above (below) the line indicates the averaged improvement for classes ranked at top (bottom) 50% in the baseline performance.