https://github.com/nlp-waseda/expr-exper-emo
공식 코드Building a Dialogue Corpus Annotated with Expressed and Experienced Emotions
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/nlp4se/review-emotion-analysis
공식 코드What About Emotions? Guiding Fine-Grained Emotion Extraction from Mobile App Reviews
https://github.com/nlpAThits/figet-hyperbolic-space
공식 코드https://github.com/nlpwm-whu/mplp
공식 코드Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and Paraphrasing
https://github.com/nmevenkamp/pcams
공식 코드Variational Multi-Phase Segmentation using High-Dimensional Local Features
https://github.com/nomuramasahir0/crfmnes
공식 코드Fast Moving Natural Evolution Strategy for High-Dimensional Problems
https://github.com/nrel/diversity_sr
공식 코드Adversarial sampling of unknown and high-dimensional conditional distributions
https://github.com/nrel/nfp
공식 코드Message-passing neural networks for high-throughput polymer screening
https://github.com/nttcslab-nlp/doc_lm
공식 코드https://github.com/numediart/EmoV-DB
공식 코드The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation Systems
https://github.com/nustm/chatgpt-sentiment-evaluation
공식 코드https://github.com/nustm/semeval-2024_ecac
공식 코드SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations
https://github.com/nxsEdson/MLCR
공식 코드Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition
https://github.com/nyukat/GLAM
공식 코드Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis
https://github.com/ojrlopez27/multiuser-framework
공식 코드https://github.com/olawod/freevc
공식 코드FreeVC: Towards High-Quality Text-Free One-Shot Voice Conversion
https://github.com/olha-kaminska/frnn_emotion_detection
공식 코드Fuzzy-Rough Nearest Neighbour Approaches for Emotion Detection in Tweets
https://github.com/olivesgatech/introspective-learning
공식 코드Introspective Learning : A Two-Stage Approach for Inference in Neural Networks
https://github.com/olivia-w12/patchdct
공식 코드PatchDCT: Patch Refinement for High Quality Instance Segmentation
https://github.com/omidmnezami/pick-object-attack
공식 코드Pick-Object-Attack: Type-Specific Adversarial Attack for Object Detection
https://github.com/open-mmlab/OpenPCDet
공식 코드Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
https://github.com/openXBOW/openXBOW
공식 코드openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit
https://github.com/openai/deeptype
공식 코드DeepType: Multilingual Entity Linking by Neural Type System Evolution
https://github.com/opencobra/COBRA.jl
공식 코드DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia
https://github.com/orchidchetiaphukan/multilingualptm_add_naacl24
공식 코드https://github.com/oscarclivio/neuralscorematching
공식 코드https://github.com/p-lambda/jukemir
공식 코드Codified audio language modeling learns useful representations for music information retrieval
https://github.com/palvj/subsage
공식 코드Inferring feature importance with uncertainties in high-dimensional data
https://github.com/panpanfei/Bringing-a-Blurry-Frame-Alive-at-High-Frame-Rate-with-an-Event-Camera
공식 코드High Frame Rate Video Reconstruction based on an Event Camera
https://github.com/pardoalejo/moviecuts
공식 코드MovieCuts: A New Dataset and Benchmark for Cut Type Recognition
https://github.com/parishadbehnam/social-biases-in-bert-variants-across-multiple-languages
공식 코드An Analysis of Social Biases Present in BERT Variants Across Multiple Languages
https://github.com/paritybit-ai/xfl
공식 코드XFL: A High Performace, Lightweighted Federated Learning Framework
https://github.com/patricia-pereira/cd-erc
공식 코드Context-Dependent Embedding Utterance Representations for Emotion Recognition in Conversations
https://github.com/patricia-pereira/deep-emotion-recognition-in-textual-conversations
공식 코드https://github.com/paul-rottger/annotation-paradigms
공식 코드Two Contrasting Data Annotation Paradigms for Subjective NLP Tasks
https://github.com/pavancm/LIVE-HFR
공식 코드Subjective and Objective Quality Assessment of High Frame Rate Videos
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.