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 21012125 of 2759 papers

TitleStatusHype
Cycle-Contrast for Self-Supervised Video Representation Learning0
DARE: AI-based Diver Action Recognition System using Multi-Channel CNNs for AUV Supervision0
Dark Transformer: A Video Transformer for Action Recognition in the Dark0
Data Collection-free Masked Video Modeling0
Data-Folding and Hyperspace Coding for Multi-Dimensonal Time-Series Data Imaging0
DAVE: Diverse Atomic Visual Elements Dataset with High Representation of Vulnerable Road Users in Complex and Unpredictable Environments0
DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition0
Deception Detection in Videos0
Decision Support for Video-based Detection of Flu Symptoms0
Decoupled Prompt-Adapter Tuning for Continual Activity Recognition0
Deep Action- and Context-Aware Sequence Learning for Activity Recognition and Anticipation0
DeepActsNet: Spatial and Motion features from Face, Hands, and Body Combined with Convolutional and Graph Networks for Improved Action Recognition0
Deep-Aligned Convolutional Neural Network for Skeleton-based Action Recognition and Segmentation0
Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition0
Deep Bilinear Learning for RGB-D Action Recognition0
Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences0
Deep Discriminative Model for Video Classification0
DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization0
DeepFN: Towards Generalizable Facial Action Unit Recognition with Deep Face Normalization0
Deep Graph Reprogramming0
Deep hierarchical pooling design for cross-granularity action recognition0
Deep Image-to-Video Adaptation and Fusion Networks for Action Recognition0
Deep Learning Approaches for Human Action Recognition in Video Data0
Deep Learning-based Action Detection in Untrimmed Videos: A Survey0
Deep learning-based approaches for human motion decoding in smart walkers for rehabilitation0
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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