https://github.com/Bkmz21/CompactCNNCascade
Compact Convolutional Neural Network Cascade for Face Detection
Papers with Code 아카이브
3D Face Reconstruction
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BonJunKu/ScooterHelmetDetector
https://github.com/BradNeuberg/personal-photos-model
https://github.com/Bsingstad/ECG-age
https://github.com/Burf/HRNetV2-OCR-Tensorflow2
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/Burf/tfdetection
https://github.com/CNC-IISER-BHOPAL/Any-Body-Can-Dance
https://github.com/CSAILVision/semantic-segmentation-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/CaedenZ/distractionModel
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/CahideSara/deneme
https://github.com/Calylyli/Mindsporehrnet
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/CatoGit/Comparing-the-Performance-of-Deepfake-Detection-Methods-on-Benchmark-Datasets
DeepFakes: a New Threat to Face Recognition? Assessment and Detection
https://github.com/CdtQin/FairFace
Improving Face Recognition from Hard Samples via Distribution Distillation Loss
https://github.com/CenIII/WSNet
https://github.com/Chang-Chia-Chi/TrackNet-Badminton-Tracking-tensorflow2
https://github.com/CharlesPikachu/CharlesFace
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/CheesyB/cpointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ChiCheng123/SRN
Selective Refinement Network for High Performance Face Detection
https://github.com/ChristianMarzahl/ObjectDetection
https://github.com/Cloud-Computing-IoT/Cloud-Enabled-Smart-Speaker
https://github.com/Cloud-Computing-IoT/speakEasy
https://github.com/Cmeijiang/PointNet_MS
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/CodeChefVIT/VOID
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/CoinCheung/pytorch-loss
Partial FC: Training 10 Million Identities on a Single Machine
https://github.com/CompVis/metric-learning-divide-and-conquer
https://github.com/CompVis/unsupervised-part-segmentation
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/Conero007/Emotion-Detection-Pytorch
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/CorentinMAG/SRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/CycloneBoy/PPDetectionPytorch
https://github.com/DChaushev/Age-Gender-Recognition
https://github.com/DELTA37/LatentKeypointGAN
https://github.com/DILiS-lab/drivers-of-predictive-aleatoric-uncertainty
FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild
https://github.com/DInesh1234-wq/tyredataset
https://github.com/DSL-FIQA/DSL-FIQA
https://github.com/Daeijavad/MAD-GAN
https://github.com/Daisy-Zhang/Face-X-ray
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.