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 2401–2450 of 2759 papers

TitleStatusHype
GraSens: A Gabor Residual Anti-aliasing Sensing Framework for Action Recognition using WiFi—0
Grounded Language Acquisition From Object and Action Imagery—0
Group-Skeleton-Based Human Action Recognition in Complex Events—0
Group sparsity and geometry constrained dictionary learning for action recognition from depth maps.—0
GTA: Global Temporal Attention for Video Action Understanding—0
GTAutoAct: An Automatic Datasets Generation Framework Based on Game Engine Redevelopment for Action Recognition—0
GTM: Gray Temporal Model for Video Recognition—0
H2O: Two Hands Manipulating Objects for First Person Interaction Recognition—0
HAA4D: Few-Shot Human Atomic Action Recognition via 3D Spatio-Temporal Skeletal Alignment—0
HAA500: Human-Centric Atomic Action Dataset with Curated Videos—0
HabitAction: A Video Dataset for Human Habitual Behavior Recognition—0
Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition with CNNs—0
Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors—0
Hand Action Detection from Ego-centric Depth Sequences with Error-correcting Hough Transform—0
Handcrafted Local Features are Convolutional Neural Networks—0
Handcrafted localized phase features for human action recognition—0
Hand Guided High Resolution Feature Enhancement for Fine-Grained Atomic Action Segmentation within Complex Human Assemblies—0
Hand-Object Interaction and Precise Localization in Transitive Action Recognition—0
Hand-Object Interaction Reasoning—0
HAPRec: Hybrid Activity and Plan Recognizer—0
Harnessing Object and Scene Semantics for Large-Scale Video Understanding—0
Harnessing the Deep Net Object Models for Enhancing Human Action Recognition—0
HAUAR: Home Automation Using Action Recognition—0
HD-EPIC: A Highly-Detailed Egocentric Video Dataset—0
Head and eye egocentric gesture recognition for human-robot interaction using eyewear cameras—0
hear-your-action: human action recognition by ultrasound active sensing—0
HENASY: Learning to Assemble Scene-Entities for Egocentric Video-Language Model—0
Heterogeneous Skeleton-Based Action Representation Learning—0
HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition—0
Hidden Markov Model: Tutorial—0
Hierarchical Action Classification with Network Pruning—0
Hierarchical Action Recognition: A Contrastive Video-Language Approach with Hierarchical Interactions—0
CoSimGNN: Towards Large-scale Graph Similarity Computation—0
Hierarchical Attention Network for Action Recognition in Videos—0
Hierarchical Compositional Representations for Few-shot Action Recognition—0
Hierarchical Contrastive Motion Learning for Video Action Recognition—0
Hierarchical Feature Aggregation Networks for Video Action Recognition—0
Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition—0
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning—0
Hierarchically Learned View-Invariant Representations for Cross-View Action Recognition—0
Hierarchical Multi-scale Attention Networks for Action Recognition—0
Hierarchical recurrent neural network for skeleton based action recognition—0
Hierarchical Self-supervised Representation Learning for Movie Understanding—0
Hierarchical Spatial Sum-Product Networks for Action Recognition in Still Images—0
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition—0
Highly Efficient Human Action Recognition with Quantum Genetic Algorithm Optimized Support Vector Machine—0
Higher-order Network for Action Recognition—0
High-order Tensor Pooling with Attention for Action Recognition—0
High Speed Human Action Recognition using a Photonic Reservoir Computer—0
Histogram of Oriented Depth Gradients for Action Recognition—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
4InternVideoTop-1 Accuracy77.2—Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6—Unverified
4VideoMAE V2-g3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
10Text4Vis3-fold Accuracy98.2—Unverified