https://github.com/hyeon-jo/PSPNet
공식 코드Self-Supervised Visual Learning by Variable Playback Speeds Prediction of a Video
Papers with Code 아카이브
Activity Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.
Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/iai-hrc/ha-vid
공식 코드HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
https://github.com/iantangc/ContrastiveLearningHAR
공식 코드Exploring Contrastive Learning in Human Activity Recognition for Healthcare
https://github.com/iantangc/SelfHAR
공식 코드SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data
https://github.com/ibm/sifar-pytorch
공식 코드https://github.com/icidsl/harflow3d
공식 코드HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices
https://github.com/ideal-idea/sap
공식 코드https://github.com/idt-iti/mmfusion-iml
공식 코드MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization
https://github.com/iduta/iresnet
공식 코드https://github.com/iduta/pyconv
공식 코드Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
https://github.com/iesymiao/cd-gcn
공식 코드A Central Difference Graph Convolutional Operator for Skeleton-Based Action Recognition
https://github.com/iit-pavis/uhar_skeletal_laplacian
공식 코드https://github.com/ilonafan/dar-noisy-labels
공식 코드Exploring Video-Based Driver Activity Recognition under Noisy Labels
https://github.com/imj2185/STAR
공식 코드https://github.com/indexfziq/comma
공식 코드https://github.com/information-fusion-lab-umass/multiwave
공식 코드https://github.com/inowlzy/smart
공식 코드SMART: Scene-motion-aware human action recognition framework for mental disorder group
https://github.com/inria-larsen/activity-recognition-prediction-wearable
공식 코드A Variational Time Series Feature Extractor for Action Prediction
https://github.com/intellabs/multimodal_cognitive_ai
공식 코드Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks
https://github.com/intelligent-computing-lab-yale/snn_har
공식 코드Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks
https://github.com/intelligolabs/sparsity_sc_ee
공식 코드Enhancing Split Computing and Early Exit Applications through Predefined Sparsity
https://github.com/interpretml/gam-changer
공식 코드Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
https://github.com/interpretml/interpret
공식 코드Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
https://github.com/iskwak/DetetctingActionStarts
공식 코드https://github.com/ispamm/josenet
공식 코드JOSENet: A Joint Stream Embedding Network for Violence Detection in Surveillance Videos
https://github.com/iurada/talos-task-arithmetic
공식 코드Efficient Model Editing with Task-Localized Sparse Fine-tuning
https://github.com/izakariyya/idg-dp
공식 코드https://github.com/j-h-hwang/temporal_shuffling
공식 코드Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks
https://github.com/jacklishufan/mamba-nd
공식 코드Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data
https://github.com/jackwu502/nsva
공식 코드https://github.com/jackyjsy/CVPR21Chal-SLR
공식 코드https://github.com/jackyjsy/sam-slr-v2
공식 코드Sign Language Recognition via Skeleton-Aware Multi-Model Ensemble
https://github.com/jacobchalk/tim
공식 코드TIM: A Time Interval Machine for Audio-Visual Action Recognition
https://github.com/jacobyuan7/din_gar
공식 코드Spatio-Temporal Dynamic Inference Network for Group Activity Recognition
https://github.com/jalayrac/object-states-action
공식 코드https://github.com/jasonforjoy/model-editing-hurt
공식 코드Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.