Face Detection Using Improved Faster RCNN
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Summary
A detailed designed Faster RCNN method named FDNet1.0 for face detection is proposed, which achieves two 1th places and one 2nd place in three tasks over WIDER FACE validation dataset.
- Type
- preprint
- Published
- 2018-02-06
- Cited by
- 80
- References
- 41
- Access
- Open access
- OpenAlex
- https://openalex.org/W2787477806
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3604941
Keywords
Pascal (unit), Computer science, Object detection, Inference, Face detection
References
- FDDB: A benchmark for face detection in unconstrained settings
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- You Only Look Once: Unified, Real-Time Object Detection
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- A deep pyramid Deformable Part Model for face detection
- A convolutional neural network cascade for face detection
- The Pascal Visual Object Classes Challenge: A Retrospective
- Aggregate channel features for multi-view face detection
- Face detection, pose estimation, and landmark localization in the wild
- Going deeper with convolutions
- Fast Human Detection Using a Cascade of Histograms of Oriented Gradients
- DenseBox: Unifying Landmark Localization with End to End Object Detection
- Robust Real-Time Face Detection
- Fast polygonal integration and its application in extending haar-like features to improve object detection
- Rethinking the Inception Architecture for Computer Vision
- Deep Residual Learning for Image Recognition
- Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
- Training Region-Based Object Detectors with Online Hard Example Mining
- Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks
- R-FCN: Object Detection via Region-based Fully Convolutional Networks
Cited by
- DSFD: Dual Shot Face Detector
- Robust Face Detection via Learning Small Faces on Hard Images
- Improved Selective Refinement Network for Face Detection
- Accurate Face Detection for High Performance
- RetinaFace: Single-stage Dense Face Localisation in the Wild
- EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
- RefineFace: Refinement Neural Network for High Performance Face Detection
- Real-Time Pre-Identification and Cascaded Detection for Tiny Faces
- CenterFace: Joint Face Detection and Alignment Using Face as Point
- Mapping Relationships and Positions of Objects in Images Using Mask and Bounding Box Data
- Feature-enhanced one-stage face detector for multiscale faces
- Recent Advances in Deep Learning for Object Detection
- SANet: Smoothed Attention Network for Single Stage Face Detector
- SEFD: A Simple and Effective Single Stage Face Detector
- YOLOv3 as a Deep Face Detector
- Multi-task Generative Adversarial Network for Detecting Small Objects in the Wild
- YOLO-face: a real-time face detector
- Investigations of Object Detection in Images/Videos Using Various Deep Learning Techniques and Embedded Platforms—A Comprehensive Review
- Detecting Multi-Scale Faces Using Attention-Based Feature Fusion and Smoothed Context Enhancement
- Detecting safety helmet wearing on construction sites with bounding‐box regression and deep transfer learning
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