Multiple Instance Detection Network with Online Instance Classifier Refinement
Huazhong University of Science and Technology
Abstract
Of late, weakly supervised object detection is with great importance in object recognition. Based on deep learning, weakly supervised detectors have achieved many promising results. However, compared with fully supervised detection, it is more challenging to train deep network based detectors in a weakly supervised manner. Here we formulate weakly supervised detection as a Multiple Instance Learning (MIL) problem, where instance classifiers (object detectors) are put into the network as hidden nodes. We propose a novel online instance classifier refinement algorithm to integrate MIL and the instance classifier refinement procedure into a single deep network, and train the network end-to-end with only…
Citation impact
- FWCI
- 16.54
- Percentile
- 100%
- References
- 54
Authors
4Topics & keywords
- Computer science
- Pascal (unit)
- Classifier (UML)
- Artificial intelligence
- Object detection
- Pattern recognition (psychology)
- Deep learning
- Detector