https://github.com/tranxuantuyen/computer
공식 코드Unified Framework with Consistency across Modalities for Human Activity Recognition
Papers with Code 아카이브
Human Activity Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 8
- 보존된 평가 기록
- 16
Classify various human activities
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tszheichoi/awesome-sensor-logger
공식 코드ALS-HAR: Harnessing Wearable Ambient Light Sensors to Enhance IMU-based Human Activity Recogntion
https://github.com/ttlmh/bridge-prompt
공식 코드Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos
https://github.com/twyncoder/vidimu-tools
공식 코드https://github.com/wang-chen/KCC
공식 코드https://github.com/wangyijunlyy/selafd
공식 코드SelaFD:Seamless Adaptation of Vision Transformer Fine-tuning for Radar-based Human Activity
https://github.com/watonomous/action-classification
공식 코드RALACs: Action Recognition in Autonomous Vehicles using Interaction Encoding and Optical Flow
https://github.com/wdkhuans/SALIENCE
공식 코드https://github.com/weiqian1/IGA
공식 코드An Interactive Greedy Approach to Group Sparsity in High Dimensions
https://github.com/xyanchen/wifi-csi-sensing-benchmark
공식 코드SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human Sensing
https://github.com/yunfengdiao/Skeleton-Robustness-Benchmark
공식 코드https://github.com/zachstarkk/asm2tv
공식 코드https://github.com/zechenli03/sensorllm
공식 코드SensorLLM: Human-Intuitive Alignment of Multivariate Sensor Data with LLMs for Activity Recognition
https://github.com/zhaxidele/har-with-snn
공식 코드Evaluating Spiking Neural Network On Neuromorphic Platform For Human Activity Recognition
https://github.com/zqiao11/tscil
공식 코드Class-incremental Learning for Time Series: Benchmark and Evaluation
https://gitlab.uni-koblenz.de/dwete/ldatopicmodels
공식 코드https://github.com/B-HAR-HumanActivityRecognition/B-HAR_Baseline-Human-Activity-Recognition
https://github.com/Bamorovat/RHM_DualStreamC3D
https://github.com/Bamorovat/RHM_OneView
https://github.com/ChetanTayal138/HAR-Web
https://github.com/DigitalBiomarkerDiscoveryPipeline/Human-Activity-Recognition
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing
https://github.com/KennCoder7/Recurrent-Attention-Network-for-HAR
https://github.com/Liut2016/stackedResBiLSTM
Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors
https://github.com/MarcRoigVilamala/DeepProbCEP
https://github.com/Pathakvishnu/Human-Activity-Recognition-
Human Activity Recognition with Convolutional Neural Netowrks
https://github.com/Peihao-Xiang/Label-Ranker
https://github.com/ShaidaMuhammad/Mukhtasir-Khail-Net
https://github.com/SonbolYb/multivariate_timeseries_dilated_conv
Multivariate Time Series Classification using Dilated Convolutional Neural Network
https://github.com/Subrata11/IoT-based-Real-time-Human-Motion-Recognition-Based-on-Skeletons-
https://github.com/TsingZ0/FL-IoT
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring
https://github.com/anskarl/LoMRF
Semi-Supervised Online Structure Learning for Composite Event Recognition
https://github.com/bornabr/CAPC
Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing
https://github.com/comp-well-org/Data_Augmentation_for_Biobehavioral_Time_Series_Data
Transformer Networks for Data Augmentation of Human Physical Activity Recognition
https://github.com/dais-ita/deepprobcep
https://github.com/facebookresearch/DomainBed
https://github.com/fangwei123456/spikingjelly
HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.