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 12511275 of 2759 papers

TitleStatusHype
Alignment-guided Temporal Attention for Video Action Recognition0
Application-Driven AI Paradigm for Human Action Recognition0
REST: REtrieve & Self-Train for generative action recognition0
Speeding Up Action Recognition Using Dynamic Accumulation of Residuals in Compressed Domain0
Low-Resolution Action Recognition for Tiny Actions Challenge0
RALACs: Action Recognition in Autonomous Vehicles using Interaction Encoding and Optical FlowCode0
Attention Spiking Neural Networks0
Ani-GIFs: A benchmark dataset for domain generalization of action recognition from GIFs0
Global Semantic Descriptors for Zero-Shot Action RecognitionCode0
Leveraging Self-Supervised Training for Unintentional Action Recognition0
View-Invariant Skeleton-based Action Recognition via Global-Local Contrastive Learning0
FuTH-Net: Fusing Temporal Relations and Holistic Features for Aerial Video Classification0
AVT: Audio-Video Transformer for Multimodal Action Recognition0
Multiscale Multimodal Transformer for Multimodal Action Recognition0
FT-HID: A Large Scale RGB-D Dataset for First and Third Person Human Interaction AnalysisCode0
Exploring Modulated Detection Transformer as a Tool for Action Recognition in VideosCode0
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition0
MECCANO: A Multimodal Egocentric Dataset for Humans Behavior Understanding in the Industrial-like Domain0
OmniVL:One Foundation Model for Image-Language and Video-Language Tasks0
Differentiable Frequency-based Disentanglement for Aerial Video Action Recognition0
Vision Transformers for Action Recognition: A Survey0
MAiVAR: Multimodal Audio-Image and Video Action Recognizer0
PoliTO-IIT-CINI Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition0
Shifting Perspective to See Difference: A Novel Multi-View Method for Skeleton based Action RecognitionCode0
Dynamic Spatio-Temporal Specialization Learning for Fine-Grained 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
4InternVideoTop-1 Accuracy77.2Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6Unverified
4VideoMAE V2-g3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified