Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection

Weakly supervised learning has emerged as a compelling tool for object detection by reducing the need for strong supervision during training. However, major challenges remain: (1) differentiation of object instances can be ambiguous; (2) detectors tend to focus on discriminative parts rather than entire objects; (3) without ground truth, object proposals have to be redundant for high recalls, causing significant memory consumption... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT BENCHMARK
Weakly Supervised Object Detection COCO test-dev wetectron(single-model, VGG16) AP50 24.8 # 1
Weakly Supervised Object Detection PASCAL VOC 2007 wetectron(single-model) MAP 54.9 # 2
Weakly Supervised Object Detection PASCAL VOC 2007 wetectron (single mode, 07+12) MAP 58.1 # 1
Weakly Supervised Object Detection PASCAL VOC 2012 test wetectron(single-model) MAP 52.1 # 1

Methods used in the Paper