DeepAI AI Chat
Log In Sign Up

Exploiting Web Images for Weakly Supervised Object Detection

by   Qingyi Tao, et al.

In recent years, the performance of object detection has advanced significantly with the evolving deep convolutional neural networks. However, the state-of-the-art object detection methods still rely on accurate bounding box annotations that require extensive human labelling. Object detection without bounding box annotations, i.e, weakly supervised detection methods, are still lagging far behind. As weakly supervised detection only uses image level labels and does not require the ground truth of bounding box location and label of each object in an image, it is generally very difficult to distill knowledge of the actual appearances of objects. Inspired by curriculum learning, this paper proposes an easy-to-hard knowledge transfer scheme that incorporates easy web images to provide prior knowledge of object appearance as a good starting point. While exploiting large-scale free web imagery, we introduce a sophisticated labour free method to construct a web dataset with good diversity in object appearance. After that, semantic relevance and distribution relevance are introduced and utilized in the proposed curriculum training scheme. Our end-to-end learning with the constructed web data achieves remarkable improvement across most object classes especially for the classes that are often considered hard in other works.


page 5

page 9


Open-Vocabulary Object Detection Using Captions

Despite the remarkable accuracy of deep neural networks in object detect...

Zero-Annotation Object Detection with Web Knowledge Transfer

Object detection is one of the major problems in computer vision, and ha...

Scalable Deep Learning Logo Detection

Existing logo detection methods usually consider a small number of logo ...

Scalable Object Detection for Stylized Objects

Following recent breakthroughs in convolutional neural networks and mono...

3D Labeling Tool

Training and testing supervised object detection models require a large ...

Weakly Supervised Faster-RCNN+FPN to classify animals in camera trap images

Camera traps have revolutionized the animal research of many species tha...

VEIL: Vetting Extracted Image Labels from In-the-Wild Captions for Weakly-Supervised Object Detection

The use of large-scale vision-language datasets is limited for object de...