https://github.com/bornabr/rscnet
공식 코드RSCNet: Dynamic CSI Compression for Cloud-based WiFi Sensing
Papers with Code 아카이브
Action Detection
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Action Detection aims to find both where and when an action occurs within a video clip and classify what the action is taking place. Typically results are given in the form of action tublets, which are action bounding boxes linked across time in the video. This is related to temporal localization, which seeks to identify the start and end frame of an action, and action recognition, which seeks only to classify which action is taking place and typically assumes a trimmed video.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bulatkh/csshar_tfa
공식 코드Temporal Feature Alignment in Contrastive Self-Supervised Learning for Human Activity Recognition
https://github.com/buptsjzhang/std-cl
공식 코드Spatial-Temporal Decoupling Contrastive Learning for Skeleton-based Human Action Recognition
https://github.com/buptsjzhang/ta-mlp
공식 코드https://github.com/butspeechfit/eend
공식 코드https://github.com/byz0e/glance-focus
공식 코드Glance and Focus: Memory Prompting for Multi-Event Video Question Answering
https://github.com/camma-public/cholectriplet2022
공식 코드https://github.com/camma-public/mcit-ig
공식 코드Surgical Action Triplet Detection by Mixed Supervised Learning of Instrument-Tissue Interactions
https://github.com/camma-public/team-or
공식 코드https://github.com/canbaoburen/CoDT
공식 코드https://github.com/carloscaetano/skeleton-images
공식 코드https://github.com/ccp-eva/sporttaskme21
공식 코드https://github.com/ccp-eva/sporttaskme22
공식 코드https://github.com/cg1177/dcan
공식 코드DCAN: Improving Temporal Action Detection via Dual Context Aggregation
https://github.com/chathukiket/evaluation-of-noise-reduction-methods
공식 코드Evaluation of Noise Reduction Methods for Sentence Recognition by Sinhala Speaking Listeners
https://github.com/chenxinyan-sg/wifi-csi-sensing-benchmark
공식 코드SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human Sensing
https://github.com/christianbresciani/nscep-spiking-NN
공식 코드https://github.com/ciaua/InstrumentPlayingDetection
공식 코드Weakly-supervised Visual Instrument-playing Action Detection in Videos
https://github.com/cogito2012/openmixer
공식 코드Exploiting VLM Localizability and Semantics for Open Vocabulary Action Detection
https://github.com/coldmanck/VidHOI
공식 코드ST-HOI: A Spatial-Temporal Baseline for Human-Object Interaction Detection in Videos
https://github.com/cruiseresearchgroup/ESPRESSO
공식 코드ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for processing heterogeneous sensor data
https://github.com/cyfml/opstl
공식 코드Exploring Self-supervised Skeleton-based Action Recognition in Occluded Environments
https://github.com/czhaneva/mst-gcn
공식 코드Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition
https://github.com/czhaneva/skelemixclr
공식 코드https://github.com/damnull/lagcn
공식 코드Language Knowledge-Assisted Representation Learning for Skeleton-Based Action Recognition
https://github.com/daniel03c1/nas_vad
공식 코드NAS-VAD: Neural Architecture Search for Voice Activity Detection
https://github.com/darkszchao/big-little_nn_strategies
공식 코드Big-Little Adaptive Neural Networks on Low-Power Near-Subthreshold Processors
https://github.com/daspraty/stg-gradcam
공식 코드Towards a geometric understanding of Spatio Temporal Graph Convolution Networks
https://github.com/davidpujol/SADA
공식 코드SADA: Semantic adversarial unsupervised domain adaptation for Temporal Action Localization
https://github.com/dazhang-cv/S3D
공식 코드S3D: Single Shot multi-Span Detector via Fully 3D Convolutional Networks
https://github.com/dbouchabou/using-language-model-to-bootstrap-human-activity-recognition-in-smart-homes
공식 코드Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes
https://github.com/debashish-saha1/HAR_UCI_DATASET_MISSING_DATA
공식 코드Activity and Subject Detection for UCI HAR Dataset with & without missing Sensor Data
https://github.com/decisionforce/VTHCL
공식 코드https://github.com/deeeeeeplearning/jadce
공식 코드Gan-Based Joint Activity Detection and Channel Estimation For Grant-free Random Access
https://github.com/deepinmotion/autogcn
공식 코드AutoGCN -- Towards Generic Human Activity Recognition with Neural Architecture Search
https://github.com/deepinmotion/shapgcn
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.