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 1751–1800 of 2759 papers

TitleStatusHype
Simultaneous Detection and Interaction Reasoning for Object-Centric Action Recognition—0
Single Image Action Recognition by Predicting Space-Time Saliency—0
Single Image Action Recognition using Semantic Body Part Actions—0
SITAR: Semi-supervised Image Transformer for Action Recognition—0
Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks—0
Skeletal quads: Human action recognition using joint quadruples—0
Skeleton-based action analysis for ADHD diagnosis—0
Skeleton-based Action Recognition of People Handling Objects—0
Skeleton-based Action Recognition through Contrasting Two-Stream Spatial-Temporal Networks—0
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates—0
Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep cnn—0
Skeleton Based Action Recognition using a Stacked Denoising Autoencoder with Constraints of Privileged Information—0
Skeleton-based Action Recognition Using LSTM and CNN—0
Skeleton-Based Action Recognition with Synchronous Local and Non-local Spatio-temporal Learning and Frequency Attention—0
Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning—0
Skeleton based Activity Recognition by Fusing Part-wise Spatio-temporal and Attention Driven Residues—0
Skeleton-based Human Action Recognition via Convolutional Neural Networks (CNN)—0
Skeleton-Based Human Action Recognition with Global Context-Aware Attention LSTM Networks—0
Skeleton-Based Mutually Assisted Interacted Object Localization and Human Action Recognition—0
Relational Network for Skeleton-Based Action Recognition—0
Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space—0
Skeleton Boxes: Solving skeleton based action detection with a single deep convolutional neural network—0
Skeleton Cloud Colorization for Unsupervised 3D Action Representation Learning—0
SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition—0
Skeletonnet: Mining deep part features for 3-d action recognition—0
Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition—0
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models—0
SkeleTR: Towards Skeleton-based Action Recognition in the Wild—0
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild—0
SkelMamba: A State Space Model for Efficient Skeleton Action Recognition of Neurological Disorders—0
Skepxels: Spatio-temporal Image Representation of Human Skeleton Joints for Action Recognition—0
Skimming and Scanning for Untrimmed Video Action Recognition—0
Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking—0
Sliding Dictionary Based Sparse Representation For Action Recognition—0
Slow and steady feature analysis: higher order temporal coherence in video—0
Slow Feature Analysis for Human Action Recognition—0
SMAM: Self and Mutual Adaptive Matching for Skeleton-Based Few-Shot Action Recognition—0
SMART Frame Selection for Action Recognition—0
SMART: Skeletal Motion Action Recognition aTtack—0
SMART-Vision: Survey of Modern Action Recognition Techniques in Vision—0
Smoothed Gaussian Mixture Models for Video Classification and Recommendation—0
SNN-Driven Multimodal Human Action Recognition via Event Camera and Skeleton Data Fusion—0
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
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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