DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations (Supplementary Material) Ximeng Sun 1 Ping Hu1 Kate Saenko Boston University, 2

Neural Information Processing Systems 

In this section, we provide the average per-class and average overall precisions (CP and OP), recalls (CR and oR) and F1 scores (CF1 and OF1) of DualCoOp in the experiment of MLR with Partial Labels on MS-COCO [3], VOC2007 [2] and BigEarth [1] (see Table 3, 4 and 5 in supplementary material) as a supplementary for Table?? and?? in the main paper. We have visualized the class-specific region feature aggregation on MS-COCO dataset (in Figure 1). We can see DualCoOp generates the high attention score at the correct objects. The pascal visual object classes (voc) challenge.

Similar Docs  Excel Report  more

TitleSimilaritySource
None found