SOTAVerified

Action Recognition

Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.

In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.

Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.

Papers

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Showing 1401–1450 of 2759 papers

TitleStatusHype
SOAR: Self-supervision Optimized UAV Action Recognition with Efficient Object-Aware Pretraining—0
SoccerKDNet: A Knowledge Distillation Framework for Action Recognition in Soccer Videos—0
Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition—0
SOS! Self-supervised Learning Over Sets Of Handled Objects In Egocentric Action Recognition—0
Space-Time Tree Ensemble for Action Recognition—0
Sparse and Low-Rank High-Order Tensor Regression via Parallel Proximal Method—0
Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition—0
Sparse Coding on Symmetric Positive Definite Manifolds using Bregman Divergences—0
Sparse Dictionary-based Attributes for Action Recognition and Summarization—0
Sparse Models for Machine Learning—0
Sparse Semi-Supervised Action Recognition with Active Learning—0
Spatial Residual Layer and Dense Connection Block Enhanced Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition—0
Spatial-Temporal Alignment Network for Action Recognition and Detection—0
Spatial-Temporal Alignment Network for Action Recognition—0
Spatial-Temporal Pyramid Graph Reasoning for Action Recognition—0
Spatial-Temporal Transformer for 3D Point Cloud Sequences—0
Spatial-temporal Transformer-guided Diffusion based Data Augmentation for Efficient Skeleton-based Action Recognition—0
Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition—0
Spatio-temporal Action Recognition: A Survey—0
Spatiotemporal Attention-based Semantic Compression for Real-time Video Recognition—0
Frequency Selective Augmentation for Video Representation Learning—0
Spatio-temporal Aware Non-negative Component Representation for Action Recognition—0
Spatio-temporal Contrastive Domain Adaptation for Action Recognition—0
Spatiotemporal Decouple-and-Squeeze Contrastive Learning for Semi-Supervised Skeleton-based Action Recognition—0
Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition—0
Spatio-Temporal FAST 3D Convolutions for Human Action Recognition—0
Spatiotemporal Filtering for Event-Based Action Recognition—0
SpatioTemporal Focus for Skeleton-based Action Recognition—0
Spatiotemporal Fusion in 3D CNNs: A Probabilistic View—0
Spatio-Temporal Fusion Networks for Action Recognition—0
Spatio-Temporal Graph Complementary Scattering Networks—0
Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition—0
Spatiotemporal graph routing for skeleton-based action recognition—0
Spatio-temporal Human Action Localisation and Instance Segmentation in Temporally Untrimmed Videos—0
Spatio-Temporal Human Action Recognition Modelwith Flexible-interval Sampling and Normalization—0
Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks—0
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition—0
Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding—0
Spatiotemporal Modeling Encounters 3D Medical Image Analysis: Slice-Shift UNet with Multi-View Fusion—0
Spatio-Temporal Pyramid Graph Convolutions for Human Action Recognition and Postural Assessment—0
Spatiotemporal Pyramid Network for Video Action Recognition—0
Spatio-Temporal Vector of Locally Max Pooled Features for Action Recognition in Videos—0
Spatio-Temporal Video Representation Learning for AI Based Video Playback Style Prediction—0
Speech2Action: Cross-modal Supervision for Action Recognition—0
Speeding Up Action Recognition Using Dynamic Accumulation of Residuals in Compressed Domain—0
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition—0
Spiking Two-Stream Methods with Unsupervised STDP-based Learning for Action Recognition—0
SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong—0
Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition—0
SSAN: Separable Self-Attention Network for Video Representation Learning—0
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All datasetsSomething-Something V2UCF101HMDB-51Something-Something V1AVA v2.2EPIC-KITCHENS-100NTU RGB+DNTU RGB+D 120Diving-48ActivityNetAVA v2.1H2O (2 Hands and Objects)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4—Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1—Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3—Unverified
4DejaVidTop-1 Accuracy77.2—Unverified
5InternVideoTop-1 Accuracy77.2—Unverified
6InternVideo2-1BTop-1 Accuracy77.1—Unverified
7VideoMAE V2-gTop-1 Accuracy77—Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7—Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5—Unverified
10TubeViT-LTop-1 Accuracy76.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7—Unverified
2OmniVec23-fold Accuracy99.6—Unverified
3VideoMAE V2-g3-fold Accuracy99.6—Unverified
4OmniVec3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
10LGD-3D Two-stream3-fold Accuracy98.2—Unverified