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 18511875 of 2759 papers

TitleStatusHype
A Large-Scale Re-identification Analysis in Sporting Scenarios: the Betrayal of Reaching a Critical Point0
A Large-Scale Robustness Analysis of Video Action Recognition Models0
A Large-scale Varying-view RGB-D Action Dataset for Arbitrary-view Human Action Recognition0
A Latent Clothing Attribute Approach for Human Pose Estimation0
ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition0
ALGO: Object-Grounded Visual Commonsense Reasoning for Open-World Egocentric Action Recognition0
Align before Adapt: Leveraging Entity-to-Region Alignments for Generalizable Video Action Recognition0
Aligning Correlation Information for Domain Adaptation in Action Recognition0
Alignment-guided Temporal Attention for Video Action Recognition0
All About Knowledge Graphs for Actions0
Alternative Semantic Representations for Zero-Shot Human Action Recognition0
AM Flow: Adapters for Temporal Processing in Action Recognition0
A Multi-Stream Bi-Directional Recurrent Neural Network for Fine-Grained Action Detection0
An Action Recognition network for specific target based on rMC and RPN0
Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms0
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks0
An Analysis of Action Recognition Datasets for Language and Vision Tasks0
An Analysis of Deep Neural Networks with Attention for Action Recognition from a Neurophysiological Perspective0
An Approach to Pose-Based Action Recognition0
An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition0
An Attention-Enhanced Recurrent Graph Convolutional Network for Skeleton-Based Action Recognition0
Anchor-Based Spatio-Temporal Attention 3D Convolutional Networks for Dynamic 3D Point Cloud Sequences0
An Effective End-to-End Solution for Multimodal Action Recognition0
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal0
An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs0
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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