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 24512475 of 2759 papers

TitleStatusHype
Histogram of Oriented Principal Components for Cross-View Action Recognition0
Hollywood 3D: Recognizing Actions in 3D Natural Scenes0
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding0
HOPC: Histogram of Oriented Principal Components of 3D Pointclouds for Action Recognition0
How can objects help action recognition?0
How Effective are Self-Supervised Models for Contact Identification in Videos0
How Object Information Improves Skeleton-based Human Action Recognition in Assembly Tasks0
Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model0
Human Action Attribute Learning From Video Data Using Low-Rank Representations0
Human Action Forecasting by Learning Task Grammars0
Human Action Performance using Deep Neuro-Fuzzy Recurrent Attention Model0
Human Action Recognition Across Datasets by Foreground-weighted Histogram Decomposition0
Human Action Recognition and Assessment via Deep Neural Network Self-Organization0
Human Action Recognition and Prediction: A Survey0
Human Action Recognition Based on Context-Dependent Graph Kernels0
Human Action Recognition Based on Multi-scale Feature Maps from Depth Video Sequences0
Human Action Recognition Based on Spatial-Temporal Attention0
Human Action Recognition from Various Data Modalities: A Review0
Human Action Recognition (HAR) Using Skeleton-based Spatial Temporal Relative Transformer Network: ST-RTR0
Human Action Recognition in Drone Videos using a Few Aerial Training Examples0
Human Action Recognition in Egocentric Perspective Using 2D Object and Hands Pose0
Human Action Recognition in Still Images Using ConViT0
Human Action Recognition: Pose-based Attention draws focus to Hands0
Human Action Recognition System using Good Features and Multilayer Perceptron Network0
Human Action Recognition using Factorized Spatio-Temporal Convolutional Networks0
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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
4DejaVidTop-1 Accuracy77.2Unverified
5InternVideoTop-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
3VideoMAE V2-g3-fold Accuracy99.6Unverified
4OmniVec3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
10LGD-3D Two-stream3-fold Accuracy98.2Unverified