Co-teaching module for multiple instance learning-based weakly supervised object detection network

Hengyu Shang

doi:10.1117/12.2684357

1 August 2023 Co-teaching module for multiple instance learning-based weakly supervised object detection network

Hengyu Shang

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127543S (2023) https://doi.org/10.1117/12.2684357
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

Weakly-supervised object detection (WSOD) is the process of detecting instances with bounding boxes in an image using only image level labels. Multiple instance learning (MIL) based networks are one of the fundamental frameworks of WSOD methods. To convert object detection to MIL proposals classification, proposal methods such as selective search windows (SSW) interpret the image as a bag of proposals. While WSOD reduces the requirement for datasets, the lack of instance-level supervision makes it challenging to constrain the proposals, which poses a considerable challenge to both the training process and the final detection accuracy. In order for training to proceed smoothly, the model often has to ignore targets with complex spatial overlap and obscure features, and focus on learning regions with distinct features. This can lead to serious problems of object missing and wrong detections. To address the aforementioned issues, this paper proposed a co-teaching structure to improve the adaptability of the model to complex scenes. This approach involves analyzing the different performance of different categories of proposals in the training process, training two deep neural networks with mutual supervision simultaneously, and controlling the back-propagation loss function while ensuring the learning ability of the original MIL network. Experimental results have demonstrated that this structure can effectively enhance the accuracy of detection and can be seamlessly integrated into other models that perform the same MIL processing.

Citation Download Citation

Hengyu Shang "Co-teaching module for multiple instance learning-based weakly supervised object detection network", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127543S (1 August 2023); https://doi.org/10.1117/12.2684357

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