{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/action-recognition-in-videos/papers/12","list_of":"/task/action-recognition-in-videos","task":"Action Recognition","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":12,"pages_in_order":28,"rows_per_page":100,"rows":[1101,1200],"of":2759,"counts":{"archive_papers_tagged":2759,"with_a_code_link":1058,"where_syntology_ran_a_sample":275,"not_listed_spam_title":0,"listed":2759,"listed_where_code_ran":275,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":232,"every_run_a_failure_of_syntologys_instrument":43,"listed_with_a_run_with_no_instrument_failure":232,"listed_every_run_a_failure_of_syntologys_instrument":43,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/action-recognition-in-videos","prev":"/task/action-recognition-in-videos/papers/11","next":"/task/action-recognition-in-videos/papers/13","papers":[{"url":null,"slug":"egosim-an-egocentric-multi-view-simulator-and","title":"EgoSim: An Egocentric Multi-view Simulator and Real Dataset for Body-worn Cameras during Motion and Activity","date":"2025-02-25","arxiv_id":"2502.18373","repositories_listed":0,"syntology":null},{"url":null,"slug":"trunk-branch-contrastive-network-with-multi","title":"Trunk-branch Contrastive Network with Multi-view Deformable Aggregation for Multi-view Action Recognition","date":"2025-02-23","arxiv_id":"2502.16493","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-hand-gesture-recognition-using","title":"Online hand gesture recognition using Continual Graph Transformers","date":"2025-02-20","arxiv_id":"2502.14939","repositories_listed":0,"syntology":null},{"url":null,"slug":"snn-driven-multimodal-human-action","title":"SNN-Driven Multimodal Human Action Recognition via Event Camera and Skeleton Data Fusion","date":"2025-02-19","arxiv_id":"2502.13385","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-timesteps-a-novel-activation-wise","title":"Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing","date":"2025-02-18","arxiv_id":"2502.12791","repositories_listed":0,"syntology":null},{"url":null,"slug":"momentseeker-a-comprehensive-benchmark-and-a","title":"MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval","date":"2025-02-18","arxiv_id":"2502.12558","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-video-understanding-deep-neural","title":"Enhancing Video Understanding: Deep Neural Networks for Spatiotemporal Analysis","date":"2025-02-11","arxiv_id":"2502.07277","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-image-to-video-an-empirical-study-of","title":"From Image to Video: An Empirical Study of Diffusion Representations","date":"2025-02-10","arxiv_id":"2502.07001","repositories_listed":0,"syntology":null},{"url":null,"slug":"hyliformer-hyperbolic-linear-attention-for","title":"HyLiFormer: Hyperbolic Linear Attention for Skeleton-based Human Action Recognition","date":"2025-02-09","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hd-epic-a-highly-detailed-egocentric-video","title":"HD-EPIC: A Highly-Detailed Egocentric Video Dataset","date":"2025-02-06","arxiv_id":"2502.04144","repositories_listed":0,"syntology":null},{"url":null,"slug":"albar-adversarial-learning-approach-to","title":"ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition","date":"2025-01-31","arxiv_id":"2502.00156","repositories_listed":0,"syntology":null},{"url":null,"slug":"recognize-any-surgical-object-unleashing-the","title":"Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data","date":"2025-01-25","arxiv_id":"2501.15326","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-human-pose-estimation-through","title":"Optimizing Human Pose Estimation Through Focused Human and Joint Regions","date":"2025-01-24","arxiv_id":"2501.14439","repositories_listed":0,"syntology":null},{"url":null,"slug":"mv-gmn-state-space-model-for-multi-view","title":"MV-GMN: State Space Model for Multi-View Action Recognition","date":"2025-01-23","arxiv_id":"2501.13829","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-masking-background-and-object-reduce","title":"Can masking background and object reduce static bias for zero-shot action recognition?","date":"2025-01-22","arxiv_id":"2501.12681","repositories_listed":0,"syntology":null},{"url":null,"slug":"smart-vision-survey-of-modern-action","title":"SMART-Vision: Survey of Modern Action Recognition Techniques in Vision","date":"2025-01-22","arxiv_id":"2501.13066","repositories_listed":0,"syntology":null},{"url":null,"slug":"blanketgen2-fit3d-synthetic-blanket","title":"BlanketGen2-Fit3D: Synthetic Blanket Augmentation Towards Improving Real-World In-Bed Blanket Occluded Human Pose Estimation","date":"2025-01-21","arxiv_id":"2501.12318","repositories_listed":0,"syntology":null},{"url":null,"slug":"install-context-aware-instructional-task","title":"InsTALL: Context-aware Instructional Task Assistance with Multi-modal Large Language Models","date":"2025-01-21","arxiv_id":"2501.12231","repositories_listed":0,"syntology":null},{"url":null,"slug":"hfgcn-hypergraph-fusion-graph-convolutional","title":"HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition","date":"2025-01-19","arxiv_id":"2501.11007","repositories_listed":0,"syntology":null},{"url":null,"slug":"collaborative-learning-for-3d-hand-object","title":"Collaborative Learning for 3D Hand-Object Reconstruction and Compositional Action Recognition from Egocentric RGB Videos Using Superquadrics","date":"2025-01-13","arxiv_id":"2501.07100","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-summarisation-with-incident-and-context","title":"Video Summarisation with Incident and Context Information using Generative AI","date":"2025-01-08","arxiv_id":"2501.04764","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-for-video-surveillance","title":"Large Language Models for Video Surveillance Applications","date":"2025-01-06","arxiv_id":"2501.02850","repositories_listed":0,"syntology":null},{"url":null,"slug":"evolving-skeletons-motion-dynamics-in-action","title":"Evolving Skeletons: Motion Dynamics in Action Recognition","date":"2025-01-05","arxiv_id":"2501.02593","repositories_listed":0,"syntology":null},{"url":null,"slug":"event-masked-autoencoder-point-wise-action","title":"Event Masked Autoencoder: Point-wise Action Recognition with Event-Based Cameras","date":"2025-01-02","arxiv_id":"2501.01040","repositories_listed":0,"syntology":null},{"url":null,"slug":"action-detail-matters-refining-video","title":"Action Detail Matters: Refining Video Recognition with Local Action Queries","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-image-classification-a-video-benchmark","title":"Beyond Image Classification: A Video Benchmark and Dual-Branch Hybrid Discrimination Framework for Compositional Zero-Shot Learning","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fsbench-a-figure-skating-benchmark-for","title":"FSBench: A Figure Skating Benchmark for Advancing Artistic Sports Understanding","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"heterogeneous-skeleton-based-action","title":"Heterogeneous Skeleton-Based Action Representation Learning","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"loki-low-dimensional-kan-for-efficient-fine","title":"LoKi: Low-dimensional KAN for Efficient Fine-tuning Image Models","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"moda-motion-drift-augmentation-for-inertial","title":"MODA: Motion-Drift Augmentation for Inertial Human Motion Analysis","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-guided-cross-modal-prompt-learning","title":"Semantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"viewpoint-rosetta-stone-unlocking-unpaired","title":"Viewpoint Rosetta Stone: Unlocking Unpaired Ego-Exo Videos for View-invariant Representation Learning","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/frequency-aware-event-cloud-network","slug":"frequency-aware-event-cloud-network","title":"Frequency-aware Event Cloud Network","date":"2024-12-30","arxiv_id":"2412.20803","repositories_listed":0,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":7,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/frequency-aware-event-cloud-network#ran","syntology_url":"https://syntology.ai/paper/2412.20803","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.20803"}},"official":null}},{"url":null,"slug":"dave-diverse-atomic-visual-elements-dataset","title":"DAVE: Diverse Atomic Visual Elements Dataset with High Representation of Vulnerable Road Users in Complex and Unpredictable Environments","date":"2024-12-28","arxiv_id":"2412.20042","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-domain-incremental-learning-for-human","title":"Video Domain Incremental Learning for Human Action Recognition in Home Environments","date":"2024-12-22","arxiv_id":"2412.16946","repositories_listed":0,"syntology":null},{"url":null,"slug":"facts-fine-grained-action-classification-for","title":"FACTS: Fine-Grained Action Classification for Tactical Sports","date":"2024-12-21","arxiv_id":"2412.16454","repositories_listed":0,"syntology":null},{"url":"/paper/msa-gcn-exploiting-multi-scale-temporal","slug":"msa-gcn-exploiting-multi-scale-temporal","title":"MSA-GCN: Exploiting Multi-Scale Temporal Dynamics With Adaptive Graph Convolution for Skeleton-Based Action Recognition","date":"2024-12-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"compactflownet-efficient-real-time-optical","title":"CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices","date":"2024-12-17","arxiv_id":"2412.13273","repositories_listed":0,"syntology":null},{"url":null,"slug":"future-aspects-in-human-action-recognition","title":"Future Aspects in Human Action Recognition: Exploring Emerging Techniques and Ethical Influences","date":"2024-12-17","arxiv_id":"2412.12990","repositories_listed":0,"syntology":null},{"url":null,"slug":"manta-enhancing-mamba-for-few-shot-action","title":"Manta: Enhancing Mamba for Few-Shot Action Recognition of Long Sub-Sequence","date":"2024-12-10","arxiv_id":"2412.07481","repositories_listed":0,"syntology":null},{"url":null,"slug":"ccs-continuous-learning-for-customized","title":"CCS: Continuous Learning for Customized Incremental Wireless Sensing Services","date":"2024-12-06","arxiv_id":"2412.04821","repositories_listed":0,"syntology":null},{"url":null,"slug":"proximal-control-of-uavs-with-federated","title":"Proximal Control of UAVs with Federated Learning for Human-Robot Collaborative Domains","date":"2024-12-03","arxiv_id":"2412.02863","repositories_listed":0,"syntology":null},{"url":null,"slug":"edgeoar-real-time-online-action-recognition","title":"EdgeOAR: Real-time Online Action Recognition On Edge Devices","date":"2024-12-02","arxiv_id":"2412.01267","repositories_listed":0,"syntology":null},{"url":null,"slug":"skelmamba-a-state-space-model-for-efficient","title":"SkelMamba: A State Space Model for Efficient Skeleton Action Recognition of Neurological Disorders","date":"2024-11-29","arxiv_id":"2411.19544","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-end-to-end-two-stream-network-based-on-rgb","title":"An End-to-End Two-Stream Network Based on RGB Flow and Representation Flow for Human Action Recognition","date":"2024-11-27","arxiv_id":"2411.18002","repositories_listed":0,"syntology":null},{"url":null,"slug":"eventcrab-harnessing-frame-and-point-synergy","title":"EventCrab: Harnessing Frame and Point Synergy for Event-based Action Recognition and Beyond","date":"2024-11-27","arxiv_id":"2411.18328","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-hyper-graph-convolution-network-for","title":"Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections","date":"2024-11-22","arxiv_id":"2411.14796","repositories_listed":0,"syntology":null},{"url":null,"slug":"when-spatial-meets-temporal-in-action","title":"When Spatial meets Temporal in Action Recognition","date":"2024-11-22","arxiv_id":"2411.15284","repositories_listed":0,"syntology":null},{"url":null,"slug":"rethinking-top-probability-from-multi-view","title":"Rethinking Top Probability from Multi-view for Distracted Driver Behaviour Localization","date":"2024-11-19","arxiv_id":"2411.12525","repositories_listed":0,"syntology":null},{"url":null,"slug":"neuron-learning-context-aware-evolving","title":"Neuron: Learning Context-Aware Evolving Representations for Zero-Shot Skeleton Action Recognition","date":"2024-11-18","arxiv_id":"2411.11288","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-to-task-learning-via-motion-guided","title":"Video-to-Task Learning via Motion-Guided Attention for Few-Shot Action Recognition","date":"2024-11-18","arxiv_id":"2411.11335","repositories_listed":0,"syntology":null},{"url":null,"slug":"extended-multi-stream-temporal-attention","title":"Extended multi-stream temporal-attention module for skeleton-based human action recognition (HAR)","date":"2024-11-10","arxiv_id":"2411.06553","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-rwkv-video-action-recognition-based","title":"Video RWKV:Video Action Recognition Based RWKV","date":"2024-11-08","arxiv_id":"2411.05636","repositories_listed":0,"syntology":null},{"url":"/paper/am-flow-adapters-for-temporal-processing-in","slug":"am-flow-adapters-for-temporal-processing-in","title":"AM Flow: Adapters for Temporal Processing in Action Recognition","date":"2024-11-04","arxiv_id":"2411.02065","repositories_listed":0,"syntology":null},{"url":null,"slug":"arn-lstm-a-multi-stream-attention-based-model","title":"ARN-LSTM: A Multi-Stream Fusion Model for Skeleton-based Action Recognition","date":"2024-11-04","arxiv_id":"2411.01769","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-action-recognition-har-using-skeleton","title":"Human Action Recognition (HAR) Using Skeleton-based Spatial Temporal Relative Transformer Network: ST-RTR","date":"2024-10-31","arxiv_id":"2410.23806","repositories_listed":0,"syntology":null},{"url":null,"slug":"love-in-action-gamifying-public-video-cameras","title":"Love in Action: Gamifying Public Video Cameras for Fostering Social Relationships in Real World","date":"2024-10-31","arxiv_id":"2411.10449","repositories_listed":0,"syntology":null},{"url":null,"slug":"recovering-complete-actions-for-cross-dataset","title":"Recovering Complete Actions for Cross-dataset Skeleton Action Recognition","date":"2024-10-31","arxiv_id":"2410.23641","repositories_listed":0,"syntology":null},{"url":null,"slug":"atgcn-a-graph-convolutional-network-for","title":"AtGCN: A Graph Convolutional Network For Ataxic Gait Detection","date":"2024-10-30","arxiv_id":"2410.22862","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-action-recognition-in-surveillance","title":"Zero-Shot Action Recognition in Surveillance Videos","date":"2024-10-28","arxiv_id":"2410.21113","repositories_listed":0,"syntology":null},{"url":null,"slug":"exocentric-to-egocentric-transfer-for-action","title":"Egocentric and Exocentric Methods: A Short Survey","date":"2024-10-27","arxiv_id":"2410.20621","repositories_listed":0,"syntology":null},{"url":null,"slug":"idempotent-unsupervised-representation","title":"Idempotent Unsupervised Representation Learning for Skeleton-Based Action Recognition","date":"2024-10-27","arxiv_id":"2410.20349","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-for-action","title":"Unsupervised Domain Adaptation for Action Recognition via Self-Ensembling and Conditional Embedding Alignment","date":"2024-10-23","arxiv_id":"2410.17489","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-visual-language-models-effective-in","title":"Are Visual-Language Models Effective in Action Recognition? A Comparative Study","date":"2024-10-22","arxiv_id":"2410.17149","repositories_listed":0,"syntology":null},{"url":null,"slug":"masked-differential-privacy","title":"Activity Recognition on Avatar-Anonymized Datasets with Masked Differential Privacy","date":"2024-10-22","arxiv_id":"2410.17098","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-the-multi-label-atomic-activity","title":"Improving the Multi-label Atomic Activity Recognition by Robust Visual Feature and Advanced Attention @ ROAD++ Atomic Activity Recognition 2024","date":"2024-10-21","arxiv_id":"2410.16037","repositories_listed":0,"syntology":null},{"url":null,"slug":"storyboard-guided-alignment-for-fine-grained","title":"Storyboard guided Alignment for Fine-grained Video Action Recognition","date":"2024-10-18","arxiv_id":"2410.14238","repositories_listed":0,"syntology":null},{"url":null,"slug":"continual-learning-improves-zero-shot-action","title":"Continual Learning Improves Zero-Shot Action Recognition","date":"2024-10-14","arxiv_id":"2410.10497","repositories_listed":0,"syntology":null},{"url":null,"slug":"eitnet-an-iot-enhanced-framework-for-real","title":"EITNet: An IoT-Enhanced Framework for Real-Time Basketball Action Recognition","date":"2024-10-13","arxiv_id":"2410.09954","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-stone-toolmaking-action-grammar-hstag-a","title":"Human Stone Toolmaking Action Grammar (HSTAG): A Challenging Benchmark for Fine-grained Motor Behavior Recognition","date":"2024-10-10","arxiv_id":"2410.08410","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-spatio-temporal-relations-in","title":"Understanding Spatio-Temporal Relations in Human-Object Interaction using Pyramid Graph Convolutional Network","date":"2024-10-10","arxiv_id":"2410.07912","repositories_listed":0,"syntology":null},{"url":null,"slug":"fourier-based-action-recognition-for-wildlife","title":"Fourier-based Action Recognition for Wildlife Behavior Quantification with Event Cameras","date":"2024-10-09","arxiv_id":"2410.06698","repositories_listed":0,"syntology":null},{"url":null,"slug":"actionatlas-a-videoqa-benchmark-for-domain","title":"ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition","date":"2024-10-08","arxiv_id":"2410.05774","repositories_listed":0,"syntology":null},{"url":null,"slug":"shadow-augmentation-for-handwashing-action","title":"Shadow Augmentation for Handwashing Action Recognition: from Synthetic to Real Datasets","date":"2024-10-04","arxiv_id":"2410.03984","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-supervised-human-action-recognition","title":"LS-HAR: Language Supervised Human Action Recognition with Salient Fusion, Construction Sites as a Use-Case","date":"2024-10-02","arxiv_id":"2410.01962","repositories_listed":0,"syntology":null},{"url":null,"slug":"surgpetl-parameter-efficient-image-to","title":"SurgPETL: Parameter-Efficient Image-to-Surgical-Video Transfer Learning for Surgical Phase Recognition","date":"2024-09-30","arxiv_id":"2409.20083","repositories_listed":0,"syntology":null},{"url":null,"slug":"eagle-egocentric-aggregated-language-video","title":"EAGLE: Egocentric AGgregated Language-video Engine","date":"2024-09-26","arxiv_id":"2409.17523","repositories_listed":0,"syntology":null},{"url":null,"slug":"soar-self-supervision-optimized-uav-action","title":"SOAR: Self-supervision Optimized UAV Action Recognition with Efficient Object-Aware Pretraining","date":"2024-09-26","arxiv_id":"2409.18300","repositories_listed":0,"syntology":null},{"url":null,"slug":"path-adaptive-spatio-temporal-state-space","title":"Path-adaptive Spatio-Temporal State Space Model for Event-based Recognition with Arbitrary Duration","date":"2024-09-25","arxiv_id":"2409.16953","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-skeleton-based-action-recognition-1","title":"Zero-Shot Skeleton-based Action Recognition with Dual Visual-Text Alignment","date":"2024-09-22","arxiv_id":"2409.14336","repositories_listed":0,"syntology":null},{"url":null,"slug":"egocentric-zone-aware-action-recognition","title":"Egocentric zone-aware action recognition across environments","date":"2024-09-21","arxiv_id":"2409.14205","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-action-recognition-on-hard-to","title":"Interpretable Action Recognition on Hard to Classify Actions","date":"2024-09-19","arxiv_id":"2409.13091","repositories_listed":0,"syntology":null},{"url":null,"slug":"distillation-free-scaling-of-large-ssms-for","title":"StableMamba: Distillation-free Scaling of Large SSMs for Images and Videos","date":"2024-09-18","arxiv_id":"2409.11867","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-audio-narrations-to-strengthen","title":"Integrating Audio Narrations to Strengthen Domain Generalization in Multimodal First-Person Action Recognition","date":"2024-09-15","arxiv_id":"2409.09611","repositories_listed":0,"syntology":null},{"url":null,"slug":"childplay-hand-a-dataset-of-hand","title":"ChildPlay-Hand: A Dataset of Hand Manipulations in the Wild","date":"2024-09-14","arxiv_id":"2409.09319","repositories_listed":0,"syntology":null},{"url":null,"slug":"kan-hyperpointnet-for-point-cloud-sequence","title":"KAN-HyperpointNet for Point Cloud Sequence-Based 3D Human Action Recognition","date":"2024-09-14","arxiv_id":"2409.09444","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-the-concept-hierarchy-for-household","title":"Using The Concept Hierarchy for Household Action Recognition","date":"2024-09-13","arxiv_id":"2409.08853","repositories_listed":0,"syntology":null},{"url":null,"slug":"2d-bidirectional-gated-recurrent-unit","title":"2D bidirectional gated recurrent unit convolutional Neural networks for end-to-end violence detection In videos","date":"2024-09-11","arxiv_id":"2409.07588","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-collection-free-masked-video-modeling","title":"Data Collection-free Masked Video Modeling","date":"2024-09-10","arxiv_id":"2409.06665","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-human-action-recognition-on","title":"Real-Time Human Action Recognition on Embedded Platforms","date":"2024-09-09","arxiv_id":"2409.05662","repositories_listed":0,"syntology":null},{"url":null,"slug":"sitar-semi-supervised-image-transformer-for","title":"SITAR: Semi-supervised Image Transformer for Action Recognition","date":"2024-09-04","arxiv_id":"2409.02910","repositories_listed":0,"syntology":null},{"url":null,"slug":"unfolding-videos-dynamics-via-taylor","title":"Unfolding Videos Dynamics via Taylor Expansion","date":"2024-09-04","arxiv_id":"2409.02371","repositories_listed":0,"syntology":null},{"url":null,"slug":"action-based-adhd-diagnosis-in-video","title":"Action-Based ADHD Diagnosis in Video","date":"2024-09-03","arxiv_id":"2409.02261","repositories_listed":0,"syntology":null},{"url":null,"slug":"adhd-diagnosis-based-on-action","title":"ADHD diagnosis based on action characteristics recorded in videos using machine learning","date":"2024-09-03","arxiv_id":"2409.02274","repositories_listed":0,"syntology":null},{"url":null,"slug":"finepseudo-improving-pseudo-labelling-through","title":"FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition","date":"2024-09-02","arxiv_id":"2409.01448","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-enhanced-zero-shot-action-recognition-a","title":"Text-Enhanced Zero-Shot Action Recognition: A training-free approach","date":"2024-08-29","arxiv_id":"2408.16412","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-pre-training-with-long-form-videos","title":"Online pre-training with long-form videos","date":"2024-08-28","arxiv_id":"2408.15651","repositories_listed":0,"syntology":null},{"url":null,"slug":"habitaction-a-video-dataset-for-human","title":"HabitAction: A Video Dataset for Human Habitual Behavior Recognition","date":"2024-08-24","arxiv_id":"2408.13463","repositories_listed":0,"syntology":null},{"url":null,"slug":"frame-order-matters-a-temporal-sequence-aware","title":"Frame Order Matters: A Temporal Sequence-Aware Model for Few-Shot Action Recognition","date":"2024-08-22","arxiv_id":"2408.12475","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-temporal-pooling-for-improving-skeleton","title":"Joint Temporal Pooling for Improving Skeleton-based Action Recognition","date":"2024-08-18","arxiv_id":"2408.09356","repositories_listed":0,"syntology":null}],"record_sha256":"1812bea37fe0af666d3e19d367a105146b30cc6d91f8d61560916ecfd54b1b31","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}