https://github.com/alsgkals2/CoReD_Released
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation
Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/alsgkals2/cored
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation
https://github.com/altndrr/persona
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/altomator/Introduction_to_Deep_Learning-2-Face_Detection
https://github.com/alvarobartt/serving-pytorch-models
https://github.com/alvinwan/shiftresnet-cifar
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
https://github.com/amamov/vgg16-vs-resnet
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/aman-arya/Any-Body-Can-Dance
https://github.com/aman-garg0001/fruit-classifier
https://github.com/amanshenoy/pose-invariant-face-recognition
https://github.com/amazon-research/long-short-term-transformer
https://github.com/amazon-science/long-short-term-transformer
https://github.com/ambityga/memsem
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/amdegroot/ssd.pytorch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/aminekha/AI-For-2022
https://github.com/amirhfarzaneh/dacl
https://github.com/amittiwary42/target-detection-eeg-signals
https://github.com/amogh7joshi/engagement-detection
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/amogh7joshi/fer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/amogh7joshi/media-vision
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/amogh7joshi/plant-health-detection
https://github.com/anax32/dimensionality-reduction
https://github.com/andersoncarlosfs/image_classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/andreas128/NTIRE21_Learning_SR_Space
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution
https://github.com/andreasveit/densenet-pytorch
https://github.com/andrijdavid/clinical-brain-interface-2020
https://github.com/andrire/RNNASIP-pulpissimo
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
https://github.com/angelvillar96/FaceEmoji
https://github.com/anguyen8/sam
https://github.com/anhttran/3dmm_basic
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
https://github.com/anhttran/3dmm_cnn
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
https://github.com/anhtu293/Vietnamese-Celebrity-Face-Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/anibali/dsnt-pose2d
https://github.com/aniket-patra-1998/FLOWER_RECOGNITION
https://github.com/aniket03/keras_compact_bilnear_CNN
https://github.com/anirudharc/transformer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.