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 10011025 of 2759 papers

TitleStatusHype
Learning Using Privileged Information for Zero-Shot Action Recognition0
Analysis and Extensions of Adversarial Training for Video ClassificationCode0
Stand-Alone Inter-Frame Attention in Video ModelsCode1
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens0
A Training Method For VideoPose3D With Ideology of Action Recognition0
MLP-3D: A MLP-like 3D Architecture with Grouped Time MixingCode0
Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition0
PrivHAR: Recognizing Human Actions From Privacy-preserving Lens0
Revealing Single Frame Bias for Video-and-Language LearningCode2
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic InformationCode1
3D Convolutional with Attention for Action Recognition0
The Spike Gating Flow: A Hierarchical Structure Based Spiking Neural Network for Online Gesture RecognitionCode0
Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 20210
Egocentric Video-Language PretrainingCode2
Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment0
A Survey on Video Action Recognition in Sports: Datasets, Methods and ApplicationsCode3
Stargazer: A transformer-based driver action detection system for intelligent transportationCode1
Skeleton-based Action Recognition via Temporal-Channel AggregationCode1
PSTNet: Point Spatio-Temporal Convolution on Point Cloud SequencesCode1
MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D VideosCode1
2D versus 3D Convolutional Spiking Neural Networks Trained with Unsupervised STDP for Human Action Recognition0
AdaptFormer: Adapting Vision Transformers for Scalable Visual RecognitionCode2
Cross-Architecture Self-supervised Video Representation LearningCode1
GraSens: A Gabor Residual Anti-aliasing Sensing Framework for Action Recognition using WiFi0
Detection of Fights in Videos: A Comparison Study of Anomaly Detection and 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