https://github.com/mingtaoguo/biggan-tensorflow
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Papers with Code 아카이브
Emotion Recognition
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Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mingyuliutw/UNIT
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/mingzehuang/latentcor
High Dimensional Semiparametric Latent Graphical Model for Mixed Data
https://github.com/minhnhat93/tf-SNDCGAN
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/mink007/Emotion_Recog_Deep_Neural_Networks/blob/master/CS231N_Project_Presentation.pptx
Emotion Recognition in Audio and Video Using Deep Neural Networks
https://github.com/minus31/Portrait-segmentation
Boundary-Aware Network for Fast and High-Accuracy Portrait Segmentation
https://github.com/minyoungg/GAN-Transform-and-Project
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/minyoungg/pix2latent
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/miracle-2001/gnn4eeg
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
https://github.com/mirbostani/QA-KD-AL
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/mit-han-lab/sparsevit
SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer
https://github.com/mithunpaul08/bert_tensorflow
https://github.com/mitran27/Attention-is-all-you-Need
https://github.com/mkavim/finetune_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/mks0601/PoseFix_RELEASE
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/mlpc-ucsd/PRTR
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/moabarar/nemar
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/mocherson/aki_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/modelscope/FunCodec
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
https://github.com/moein-shariatnia/Pix2Seq
https://github.com/mohamedateya/bert-fine-tuning-sentence-classification-for-cola
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/mohammadreza-Banaei73/INLP_neural_practical_session
https://github.com/mohanliu/HRnet-semantic-segmentation-exp
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/monimoyd/NLPEnglishToPythonCodeUsingTransformer
https://github.com/monimoyd/NLPMachineTranslationUsingTransformer
https://github.com/montaserFath/Reinforcement-Learning-for-Prosthetics
https://github.com/moon23k/Scheduled_Sampling
https://github.com/moon23k/Transformer_Anchors
https://github.com/moon23k/Transformer_Archs
https://github.com/morikatron/PPO
High-Dimensional Continuous Control Using Generalized Advantage Estimation
https://github.com/moskewcz/boda
https://github.com/mpariente/asteroid
Two-Step Sound Source Separation: Training on Learned Latent Targets
https://github.com/mseg-dataset/mseg-semantic
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/mseitzer/pytorch-fid
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/mshilpaa/DenseDepth
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/msinghal34/Image-Blending-using-GP-GANs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.