Yang et al., 2019 - Google Patents

Combining YOLOV3-tiny model with dropblock for tiny-face detection

Yang et al., 2019

Document ID
2625684888539923460
Author
Yang Z
Xu W
Wang Z
He X
Yang F
Yin Z
Publication year
Publication venue
2019 IEEE 19th International Conference on Communication Technology (ICCT)

External Links

Snippet

Face detection is one of the most basic tasks in many various face applications, which is gradually becoming the most acceptable biometric recognition method. However, tinyface detection is a complex and challenging pattern detection problem that encounters many …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268Feature extraction; Face representation
    • G06K9/00281Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6256Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6201Matching; Proximity measures
    • G06K9/6202Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/40Analysis of texture
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Li et al. Contour knowledge transfer for salient object detection
Li et al. SCL-MLNet: Boosting few-shot remote sensing scene classification via self-supervised contrastive learning
George et al. Deep pixel-wise binary supervision for face presentation attack detection
Cong et al. Global-and-local collaborative learning for co-salient object detection
Mishchuk et al. Working hard to know your neighbor's margins: Local descriptor learning loss
Yang et al. Combining YOLOV3-tiny model with dropblock for tiny-face detection
Ming et al. Simple triplet loss based on intra/inter-class metric learning for face verification
WO2019153175A1 (en) Machine learning-based occluded face recognition system and method, and storage medium
Wang et al. Contrastive transformation for self-supervised correspondence learning
Zhao et al. Accurate pedestrian detection by human pose regression
Liu et al. Two-stage underwater object detection network using swin transformer
Wang et al. Multi-scale context aggregation network with attention-guided for crowd counting
CN112580502B (en) SICNN-based low-quality video face recognition method
CN108280421A (en) Human bodys' response method based on multiple features Depth Motion figure
Ullah et al. Human action recognition in videos using stable features
Zeng et al. Occlusion‐invariant face recognition using simultaneous segmentation
Li et al. Exploiting facial symmetry to expose deepfakes
Wang et al. Generative adversarial network based on resnet for conditional image restoration
Gilani et al. Towards large-scale 3D face recognition
Yaseen et al. A novel approach based on multi-level bottleneck attention modules using self-guided dropblock for person re-identification
Wu et al. Ggvit: Multistream vision transformer network in face2face facial reenactment detection
Zhu et al. A novel simple visual tracking algorithm based on hashing and deep learning
CN114492634A (en) Fine-grained equipment image classification and identification method and system
Song et al. Dense face network: A dense face detector based on global context and visual attention mechanism
Wu et al. Exploiting superpixel and hybrid hash for kernel-based visual tracking