Contextual Priming and Feedback for Faster R-CNN
نویسندگان
چکیده
The field of object detection has seen dramatic performance improvements in the last few years. Most of these gains are attributed to bottom-up, feedforward ConvNet frameworks. However, in case of humans, top-down information, context and feedback play an important role in doing object detection. This paper investigates how we can incorporate top-down information and feedback in the state-of-the-art Faster R-CNN framework. Specifically, we propose to: (a) augment Faster RCNN with a semantic segmentation network; (b) use segmentation for top-down contextual priming; (c) use segmentation to provide top-down iterative feedback using two stage training. Our results indicate that all three contributions improve the performance on object detection, semantic segmentation and region proposal generation.
منابع مشابه
T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos
The state-of-the-art performance for object detection has been significantly improved over the past two years. Besides the introduction of powerful deep neural networks such as GoogleNet [1] and VGG [2], novel object detection frameworks such as R-CNN [3] and its successors, Fast R-CNN [4] and Faster R-CNN [5], play an essential role in improving the state-of-the-art. Despite their effectivenes...
متن کاملDeep feature based contextual model for object detection
Object detection is one of the most active areas in computer vision, which has made significant improvement in recent years. Current state-of-the-art object detection methods mostly adhere to the framework of regions with convolutional neural network (R-CNN) and only use local appearance features inside object bounding boxes. Since these approaches ignore the contextual information around the o...
متن کاملDeep learning-based CAD systems for mammography: A review article
Breast cancer is one of the most common types of cancer in women. Screening mammography is a low‑dose X‑ray examination of breasts, which is conducted to detect breast cancer at early stages when the cancerous tumor is too small to be felt as a lump. Screening mammography is conducted for women with no symptoms of breast cancer, for early detection of cancer when the cancer is most treatable an...
متن کاملFace R-CNN
Faster R-CNN is one of the most representative and successful methods for object detection, and has been becoming increasingly popular in various objection detection applications. In this report, we propose a robust deep face detection approach based on Faster R-CNN. In our approach, we exploit several new techniques including new multi-task loss function design, online hard example mining, and...
متن کاملContextual Interference Effect in Bandwidth and Self-Control Feedback Conditions on Relative and Absolute Timing Learning
This study aims to better understand the effect of practice schedule and feedback providing types. In two separate experiments the contextual interference effect in bandwidth and self-control feedback conditions on relative and absolute timing learning was examined. In experiment I, the effect of contextual interference using bandwidth and self-control feedback on absolute timing learning (para...
متن کامل