https://github.com/haibo-qiu/from
공식 코드End2End Occluded Face Recognition by Masking Corrupted Features
Papers with Code 아카이브
Face Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 25
- 보존된 평가 기록
- 88
Facial Recognition is the task of making a positive identification of a face in a photo or video image against a pre-existing database of faces. It begins with detection - distinguishing human faces from other objects in the image - and then works on identification of those detected faces.
The state of the art tables for this task are contained mainly in the consistent parts of the task : the face verification and face identification tasks.
<span style="color:grey; opacity: 0.6">( Image credit: Face Verification )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/haiyuwu/ba-test-dataset
공식 코드What Should Be Balanced in a "Balanced" Face Recognition Dataset?
https://github.com/haiyuwu/facebrightness
공식 코드Face Recognition Accuracy Across Demographics: Shining a Light Into the Problem
https://github.com/haiyuwu/logicalconsistency
공식 코드Logical Consistency and Greater Descriptive Power for Facial Hair Attribute Learning
https://github.com/haiyuwu/sota-face-recognition-train-and-test
공식 코드https://github.com/hamzah-luqman/mfr
공식 코드Ensemble Learning using Transformers and Convolutional Networks for Masked Face Recognition
https://github.com/hanssuny/diffam
공식 코드DiffAM: Diffusion-based Adversarial Makeup Transfer for Facial Privacy Protection
https://github.com/hanweikung/face_anon_simple
공식 코드https://github.com/haoosz/ffr-net
공식 코드A Unified Framework for Masked and Mask-Free Face Recognition via Feature Rectification
https://github.com/hardik-uppal/teacher-student-gan
공식 코드Teacher-Student Adversarial Depth Hallucination to Improve Face Recognition
https://github.com/heathcliff-saku/dopatch
공식 코드Distributional Modeling for Location-Aware Adversarial Patches
https://github.com/hengxyz/Dynamic_multi-task-learning
공식 코드Dynamic Multi-Task Learning for Face Recognition with Facial Expression
https://github.com/hengxyz/cari-visual-recognition-via-multitask-learning
공식 코드Dynamic Deep Multi-task Learning for Caricature-Visual Face Recognition
https://github.com/hertasecurity/LTFT
공식 코드Long-Term Face Tracking for Crowded Video-Surveillance Scenarios
https://github.com/hjy1312/AGPM
공식 코드Attention-guided Progressive Mapping for Profile Face Recognition
https://github.com/hm-choi/blind-match
공식 코드https://github.com/huangyangyu/NoiseFace
공식 코드https://github.com/huangyangyu/SeqFace
공식 코드SeqFace: Make full use of sequence information for face recognition
https://github.com/hurricanelx/lrfr
공식 코드https://github.com/i13abe/Adaptive-discriminant-and-center
공식 코드https://github.com/iamsangmeng/interface
공식 코드InterFace:Adjustable Angular Margin Inter-class Loss for Deep Face Recognition
https://github.com/ibug-group/face_reid
공식 코드A real-time and unsupervised face Re-Identification system for Human-Robot Interaction
https://github.com/igsb/gestaltmatcher-arc
공식 코드Improving Deep Facial Phenotyping for Ultra-rare Disorder Verification Using Model Ensembles
https://github.com/irvingmeng/securevector
공식 코드Towards Privacy-Preserving, Real-Time and Lossless Feature Matching
https://github.com/isi-vista/face-completion
공식 코드https://github.com/ivclab/Online-Face-Recognition-and-Authentication
공식 코드Data-specific Adaptive Threshold for Face Recognition and Authentication
https://github.com/ivonacolakovic/synthgap-mitigation-using-kd-in-ffr
공식 코드How Knowledge Distillation Mitigates the Synthetic Gap in Fair Face Recognition
https://github.com/j-alex-hanson/rethinking-race-face-datasets
공식 코드Rethinking Common Assumptions to Mitigate Racial Bias in Face Recognition Datasets
https://github.com/jackie840129/fedfr
공식 코드FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition
https://github.com/jagmohaniiit/3dfacemorph
공식 코드3D Face Morphing Attacks: Generation, Vulnerability and Detection
https://github.com/jagmohaniiit/latentcompositioncode
공식 코드Deep Composite Face Image Attacks: Generation, Vulnerability and Detection
https://github.com/jankolf/grafiqs
공식 코드GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes
https://github.com/jcroh0508/flats
공식 코드Robust Smart Home Face Recognition under Starving Federated Data
https://github.com/jerryyann/dpi
공식 코드Diffusion Prior Interpolation for Flexibility Real-World Face Super-Resolution
https://github.com/jhh37/wearmask3d
공식 코드A 3D model-based approach for fitting masks to faces in the wild
https://github.com/jierunchen/tvconv
공식 코드TVConv: Efficient Translation Variant Convolution for Layout-aware Visual Processing
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.