https://github.com/WeLoveKiraboshi/In-PlaneRotation-AwareDepthEstimation
High Quality Monocular Depth Estimation via Transfer Learning
Papers with Code 아카이브
Emotion Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 12
- 평가표
- 10
- 보존된 평가 기록
- 18
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/WeLoveKiraboshi/In-PlaneRotationAwareDepthEstimation
High Quality Monocular Depth Estimation via Transfer Learning
https://github.com/WenYanger/General-Transformer-Pytorch
https://github.com/WenjieDu/PyPOTS
https://github.com/Westlake-AI/openmixup
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions
https://github.com/WittmannF/quadcopter-best-practices
https://github.com/Wolfie8935/Implementation-of-Attention-is-all-you-need
https://github.com/XINZXZHANG/Bert_repo
https://github.com/XUJitao/WordEmbedding
https://github.com/XapaJIaMnu/transformative
https://github.com/XiSHEN0220/RANSAC-Flow
https://github.com/XiaXuehai/faceboxes
https://github.com/Xinsen-Zhang/transformer
https://github.com/XuhanLiu/Transformer
https://github.com/Y1ran/NLP-BERT--ChineseVersion
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/YYGXjpg/BERT_WL
https://github.com/Yang-Q-D/mindsporeCode/tree/master/ibnnet
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/YangRui2015/Modular_HER
https://github.com/YaohuiZeng/biglasso
Hybrid safe-strong rules for efficient optimization in lasso-type problems
https://github.com/Yipeng91/text_classifier_pub
https://github.com/YoUNG824/DDPG
https://github.com/YongWookHa/BERT-on-Pytorch-Template
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Young-in/ANM-Assignment2-loglizer
Anomaly Detection using Autoencoders in High Performance Computing Systems
https://github.com/YoungXiyuan/DCA
Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss
https://github.com/Yu-Group/iterative-Random-Forest
Iterative Random Forests to detect predictive and stable high-order interactions
https://github.com/YuanEric88/bert-nlu
https://github.com/YuehChuan/bert-Agus
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/YvanG/VQGAN-CLIP
https://github.com/ZC119/richardson_tracking
https://github.com/ZVK/Talking-Heads
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/ZVK/talking_heads
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/ZZDoog/ProDubber
Prosody-Enhanced Acoustic Pre-training and Acoustic-Disentangled Prosody Adapting for Movie Dubbing
https://github.com/ZZhangyutong/fasttext
https://github.com/ZacharyChenpk/Local_ETHZ
Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss
https://github.com/ZainRaza14/deepRL
https://github.com/Zeeshan75/Bert_Telugu_Ner
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.