Papers with Code 아카이브

Emotion Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/camel-lab/arabic_error_type_annotation

공식 코드

Automatic Error Type Annotation for Arabic

https://github.com/caperock/robustai

공식 코드

Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation

https://github.com/caskcsg/spcl

공식 코드

Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversation

https://github.com/castorini/pyserini

공식 코드

Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations

https://github.com/cbg-ethz/subgroupseparation

공식 코드

High-Dimensional Inference in Bayesian Networks

https://github.com/cecile-hi/regularized-adaptive-weight-modification

공식 코드

Do You Remember? Overcoming Catastrophic Forgetting for Fake Audio Detection

https://github.com/cfredinh/cdcl

공식 코드

Metadata-guided Consistency Learning for High Content Images

https://github.com/chaejeonglee/codi

공식 코드

CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis

https://github.com/chailab-umich/GPT-4-Emotion-Annotation

공식 코드

From Text to Emotion: Unveiling the Emotion Annotation Capabilities of LLMs

https://github.com/chailab-umich/ModelingIndividualEvaluators

공식 코드

The Whole Is Bigger Than the Sum of Its Parts: Modeling Individual Annotators to Capture Emotional Variability

https://github.com/chailab-umich/uni_emotion_release

공식 코드

Contrastive Distillation of Emotion Knowledge from LLMs for Zero-Shot Emotion Recognition

https://github.com/chaimi2013/CCM

공식 코드

Towards High Performance Human Keypoint Detection

https://github.com/chen-xdu/gmss

공식 코드

GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition

https://github.com/chenbinghui1/MHN

공식 코드

Mixed High-Order Attention Network for Person Re-Identification

https://github.com/chenchao666/Contrast-enhanced-MRI-Synthesis

공식 코드

Synthesizing MR Image Contrast Enhancement Using 3D High-resolution ConvNets

https://github.com/chendrag/sfbc

공식 코드

Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling

https://github.com/chengq220/Facial_Perturb

공식 코드

Leaving Some Facial Features Behind

https://github.com/chengzju/carat

공식 코드

CARAT: Contrastive Feature Reconstruction and Aggregation for Multi-Modal Multi-Label Emotion Recognition

https://github.com/chenhongyiyang/gpvit

공식 코드

GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation

https://github.com/chenxin-dlut/transt-m

공식 코드

High-Performance Transformer Tracking

https://github.com/chenyangh/SemEval2019Task3

공식 코드

ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT

https://github.com/chincharles/u-emo

공식 코드

UniEmoX: Cross-modal Semantic-Guided Large-Scale Pretraining for Universal Scene Emotion Perception

https://github.com/chongjie-si/homi

공식 코드

Multi-label Classification with High-rank and High-order Label Correlations

https://github.com/chou141253/FGVC-HERBS

공식 코드

Fine-grained Visual Classification with High-temperature Refinement and Background Suppression

https://github.com/chrischoy/HighDimConvNets

공식 코드

High-dimensional Convolutional Networks for Geometric Pattern Recognition

https://github.com/christopher-w-murphy/Class-Imbalance-in-WW-Polarization

공식 코드

Class Imbalance Techniques for High Energy Physics

https://github.com/cimagroup/audiovisual-emotionrecognitionusingtda

공식 코드

Emotion recognition in talking-face videos using persistent entropy and neural networks

https://github.com/cjfcsjt/SILBO

공식 코드

Semi-supervised Embedding Learning for High-dimensional Bayesian Optimization

https://github.com/ckyeungac/deep-knowledge-tracing-plus

공식 코드

Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization

https://github.com/clarin-pl/chatgpt-evaluation-01-2023

공식 코드

ChatGPT: Jack of all trades, master of none

https://github.com/clarin-pl/personalized-emotion-prediction-with-normalizing-flows

공식 코드

Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows

https://github.com/clarkdinh/chusp

공식 코드

Mining compact high utility sequential patterns

https://github.com/cmb-chula/pylon

공식 코드

High resolution weakly supervised localization architectures for medical images

https://github.com/cmb-chula/recasnet

공식 코드

ReCasNet: Improving consistency within the two-stage mitosis detection framework

https://github.com/cmubig/ccub

공식 코드

Towards Equitable Representation in Text-to-Image Synthesis Models with the Cross-Cultural Understanding Benchmark (CCUB) Dataset

https://github.com/cnnlstm/fslsd_hires

공식 코드

High-resolution Face Swapping via Latent Semantics Disentanglement

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.