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

Showing 18261850 of 2759 papers

TitleStatusHype
Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events0
Exploiting Inter-Frame Regional Correlation for Efficient Action Recognition0
Streaming Object Detection for 3-D Point Clouds0
A Semantics-Guided Graph Convolutional Network for Skeleton-Based Action Recognition0
Inferring Temporal Compositions of Actions Using Probabilistic Automata0
HAPRec: Hybrid Activity and Plan Recognizer0
Can We Learn Heuristics For Graphical Model Inference Using Reinforcement Learning?0
Human and Machine Action Prediction Independent of Object Information0
Action recognition in real-world videos0
TAEN: Temporal Aware Embedding Network for Few-Shot Action Recognition0
Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition0
Combining Deep Learning Classifiers for 3D Action Recognition0
FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding0
Spatiotemporal Fusion in 3D CNNs: A Probabilistic View0
ASL Recognition with Metric-Learning based Lightweight Network0
What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition0
Human action recognition with a large-scale brain-inspired photonic computer0
Knowing What, Where and When to Look: Efficient Video Action Modeling with Attention0
Speech2Action: Cross-modal Supervision for Action Recognition0
Action Localization through Continual Predictive Learning0
Modeling Cross-view Interaction Consistency for Paired Egocentric Interaction Recognition0
Ensembles of Deep Neural Networks for Action Recognition in Still Images0
Temporal Extension Module for Skeleton-Based Action Recognition0
STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition0
Feedback Graph Convolutional Network for Skeleton-based Action Recognition0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3Unverified
4InternVideoTop-1 Accuracy77.2Unverified
5DejaVidTop-1 Accuracy77.2Unverified
6InternVideo2-1BTop-1 Accuracy77.1Unverified
7VideoMAE V2-gTop-1 Accuracy77Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5Unverified
10TubeViT-LTop-1 Accuracy76.1Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7Unverified
2OmniVec23-fold Accuracy99.6Unverified
3OmniVec3-fold Accuracy99.6Unverified
4VideoMAE V2-g3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified