Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation

Can we detect common objects in a variety of image domains without instance-level annotations? In this paper, we present a framework for a novel task, cross-domain weakly supervised object detection, which addresses this question... (read more)

PDF Abstract CVPR 2018 PDF CVPR 2018 Abstract

Results from the Paper


 Ranked #1 on Weakly Supervised Object Detection on Watercolor2k (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT BENCHMARK
Weakly Supervised Object Detection Clipart1k DT+PL MAP 46.0 # 2
Weakly Supervised Object Detection Comic2k DT+PL MAP 37.2 # 2
Weakly Supervised Object Detection Watercolor2k DT+PL MAP 54.3 # 1

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet