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 19011925 of 2759 papers

TitleStatusHype
A Real-time Action Representation with Temporal Encoding and Deep Compression0
A real-time algorithm for human action recognition in RGB and thermal video0
A Real-Time System for Egocentric Hand-Object Interaction Detection in Industrial Domains0
A Review on Coarse to Fine-Grained Animal Action Recognition0
Are Visual-Language Models Effective in Action Recognition? A Comparative Study0
Are you SURE? Enhancing Multimodal Pretraining with Missing Modalities through Uncertainty Estimation0
ARN-LSTM: A Multi-Stream Fusion Model for Skeleton-based Action Recognition0
A robust and efficient video representation for action recognition0
ARTiS: Appearance-based Action Recognition in Task Space for Real-Time Human-Robot Collaboration0
ASCNet: Self-supervised Video Representation Learning with Appearance-Speed Consistency0
A Semantics-Guided Graph Convolutional Network for Skeleton-Based Action Recognition0
A Short Overview of Multi-Modal Wi-Fi Sensing0
A Simple and Efficient Baseline for Video Action Recognition0
ASL Recognition with Metric-Learning based Lightweight Network0
A Spectral Nonlocal Block for Neural Networks0
A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 20230
A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP0
A Survey of IMU Based Cross-Modal Transfer Learning in Human Activity Recognition0
A Survey of Video-based Action Quality Assessment0
A Survey of Visual Analysis of Human Motion and Its Applications0
A Survey on 3D Skeleton-Based Action Recognition Using Learning Method0
A Survey on Backbones for Deep Video Action Recognition0
A Survey on Contrastive Self-supervised Learning0
A Survey on Human Action Recognition0
A Survey on Multimodal Wearable Sensor-based Human 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
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