Papers with Code 아카이브
Emotion Recognition
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- 평가표
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- 보존된 평가 기록
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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/vojha-code/Hierarchical-Fuzzy-Tree
공식 코드Multiobjective Programming for Type-2 Hierarchical Fuzzy Inference Trees
https://github.com/vrushank-ahire/maven_8th_abaw
공식 코드MAVEN: Multi-modal Attention for Valence-Arousal Emotion Network
https://github.com/vsl-team/EPiC-2023-ACII
공식 코드Multi-scale Transformer-based Network for Emotion Recognition from Multi Physiological Signals
https://github.com/vut-hfut/micro-action
공식 코드https://github.com/vwxyzjn/cleanrl
공식 코드CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms
https://github.com/w-wu/deer
공식 코드Estimating the Uncertainty in Emotion Attributes using Deep Evidential Regression
https://github.com/w-wu/erc-slt22
공식 코드https://github.com/w-wu/steer
공식 코드Integrating Emotion Recognition with Speech Recognition and Speaker Diarisation for Conversations
https://github.com/wadeyin9712/gd-vcr
공식 코드Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning
https://github.com/wagner-niklas/cage_expression_inference
공식 코드https://github.com/wangdongdut/Long-term-Visual-Tracking
공식 코드https://github.com/wanghangpsu/mm-bd
공식 코드https://github.com/wangjingyao07/st-f2m
공식 코드Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion Recognition
https://github.com/wangzhifengharrison/htnet
공식 코드https://github.com/watml/min-max-2nd-order
공식 코드https://github.com/wayne0908/Label-Efficient-Two-Sample
공식 코드https://github.com/wecacuee/Bayesian_CBF
공식 코드Probabilistic Safety Constraints for Learned High Relative Degree System Dynamics
https://github.com/weiqian1/IGA
공식 코드An Interactive Greedy Approach to Group Sparsity in High Dimensions
https://github.com/wenbowen123/iros20-6d-pose-tracking
공식 코드Vision-driven Compliant Manipulation for Reliable, High-Precision Assembly Tasks
https://github.com/wendazhou/alocv-package
공식 코드Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
https://github.com/wenliangdai/Modality-Transferable-MER
공식 코드Modality-Transferable Emotion Embeddings for Low-Resource Multimodal Emotion Recognition
https://github.com/wenliangdai/Multimodal-End2end-Sparse
공식 코드https://github.com/wenluvalor/arp-marp
공식 코드https://github.com/werywjw/sep-cvdl
공식 코드GiMeFive: Towards Interpretable Facial Emotion Classification
https://github.com/whaleloops/interpoetry
공식 코드https://github.com/whatissimondoing/cog-bart
공식 코드Contrast and Generation Make BART a Good Dialogue Emotion Recognizer
https://github.com/whenwen/solving-lpn-using-neural-networks
공식 코드Practically Solving LPN in High Noise Regimes Faster Using Neural Networks
https://github.com/williamyang1991/DualStyleGAN
공식 코드Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer
https://github.com/williamyang1991/vtoonify
공식 코드VToonify: Controllable High-Resolution Portrait Video Style Transfer
https://github.com/wjko2/INQUISITIVE
공식 코드Inquisitive Question Generation for High Level Text Comprehension
https://github.com/wjmaddox/mtgp_sampler
공식 코드https://github.com/wjn922/sp-tad
공식 코드Towards High-Quality Temporal Action Detection with Sparse Proposals
https://github.com/wlr737/emnlp2022-seek
공식 코드Empathetic Dialogue Generation via Sensitive Emotion Recognition and Sensible Knowledge Selection
https://github.com/wojzaremba/btest
공식 코드https://github.com/wooyoohl/mer2024-semi
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.