https://github.com/kmccurdy/w2v-gender
공식 코드Grammatical gender associations outweigh topical gender bias in crosslinguistic word embeddings
Papers with Code 아카이브
Emotion Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 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/kniter1/tailor
공식 코드Tailor Versatile Multi-modal Learning for Multi-label Emotion Recognition
https://github.com/knoriy/CLARA
공식 코드CLARA: Multilingual Contrastive Learning for Audio Representation Acquisition
https://github.com/knowledgetechnologyuhh/meld-fair
공식 코드Whose Emotion Matters? Speaking Activity Localisation without Prior Knowledge
https://github.com/kobeshegu/eccv2022_wavegan
공식 코드WaveGAN: Frequency-aware GAN for High-Fidelity Few-shot Image Generation
https://github.com/konstantinosKokos/Lassy-TLG-Supertagging
공식 코드Constructive Type-Logical Supertagging with Self-Attention Networks
https://github.com/kpandey008/DiffuseVAE
공식 코드DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
https://github.com/kpeng9510/affect-dml
공식 코드Affect-DML: Context-Aware One-Shot Recognition of Human Affect using Deep Metric Learning
https://github.com/krshay/MTD-2D
공식 코드Two-dimensional multi-target detection: an autocorrelation analysis approach
https://github.com/krshay/mtd-2d-em
공식 코드An approximate expectation-maximization for two-dimensional multi-target detection
https://github.com/krystalan/sportssum2.0
공식 코드SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary
https://github.com/ksehic/lassobench
공식 코드LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
https://github.com/kssyyy/cmcrd
공식 코드CMCRD: Cross-Modal Contrastive Representation Distillation for Emotion Recognition
https://github.com/kuhnkeF/ABAW2020TNT
공식 코드https://github.com/kuielab/mdx-net
공식 코드KUIELab-MDX-Net: A Two-Stream Neural Network for Music Demixing
https://github.com/kunli-cs/pcan
공식 코드Prototypical Calibrating Ambiguous Samples for Micro-Action Recognition
https://github.com/kwotsin/mimicry
공식 코드Exploring The Effect of High-frequency Components in GANs Training
https://github.com/l294265421/SIGIR22-TOWE
공식 코드Training Entire-Space Models for Target-oriented Opinion Words Extraction
https://github.com/language-ml/semeval2024-task3
공식 코드AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair Analysis
https://github.com/laurenceyang33/cellgoal
공식 코드Estimating Cellular Goals from High-Dimensional Biological Data
https://github.com/lclarte/uncertainty-project
공식 코드Theoretical characterization of uncertainty in high-dimensional linear classification
https://github.com/lcs2-iiitd/emnlp-coffee
공식 코드https://github.com/lei-wang-github/DeepPS2
공식 코드DeepPS2: Revisiting Photometric Stereo Using Two Differently Illuminated Images
https://github.com/leitro/labeladaptivemixup-ser
공식 코드Learning Robust Self-attention Features for Speech Emotion Recognition with Label-adaptive Mixup
https://github.com/lemei/affective-computing
공식 코드Recent Trends of Multimodal Affective Computing: A Survey from NLP Perspective
https://github.com/lemei/epo-ecpe
공식 코드Emotion Prediction Oriented method with Multiple Supervisions for Emotion-Cause Pair Extraction
https://github.com/lemei/unimse
공식 코드UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognition
https://github.com/lemire/lbimproved
공식 코드Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound
https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
공식 코드Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/leqsnan/skaig-erc
공식 코드A Hierarchical Transformer with Speaker Modeling for Emotion Recognition in Conversation
https://github.com/lequnwang/fair-two-stage-recommender
공식 코드Uncertainty Quantification for Fairness in Two-Stage Recommender Systems
https://github.com/leson502/CORECT_EMNLP2023
공식 코드https://github.com/leungsamwai/finite-expression-method
공식 코드Finite Expression Method for Solving High-Dimensional Partial Differential Equations
https://github.com/lfz/Guided-Denoise
공식 코드Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser
https://github.com/lgsvl/simulator
공식 코드LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving
https://github.com/lhoyer/hrda
공식 코드HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.