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 951975 of 2759 papers

TitleStatusHype
Video-based Human Action Recognition using Deep Learning: A Review0
AFE-CNN: 3D Skeleton-based Action Recognition with Action Feature Enhancement0
Blockwise Temporal-Spatial Pathway Network0
Expanding Language-Image Pretrained Models for General Video RecognitionCode3
Privacy-Preserving Action Recognition via Motion Difference QuantizationCode1
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition0
Two-Stream Transformer Architecture for Long Video Understanding0
Object-ABN: Learning to Generate Sharp Attention Maps for Action Recognition0
Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action RecognitionCode1
SSIVD-Net: A Novel Salient Super Image Classification & Detection Technique for Weaponized ViolenceCode1
P2ANet: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos0
Unsupervised Domain Adaptation for Video Transformers in Action RecognitionCode0
MAR: Masked Autoencoders for Efficient Action RecognitionCode1
Intelligent 3D Network Protocol for Multimedia Data Classification using Deep Learning0
AE-Net:Adjoint Enhancement Network for Efficient Action Recognition in Video Understanding0
Temporal Saliency Query Network for Efficient Video Recognition0
Real-Time Elderly Monitoring for Senior Safety by Lightweight Human Action Recognition0
NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition0
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
Task-adaptive Spatial-Temporal Video Sampler for Few-shot Action RecognitionCode1
Hierarchically Self-Supervised Transformer for Human Skeleton Representation LearningCode1
GOCA: Guided Online Cluster Assignment for Self-Supervised Video Representation LearningCode0
Discover and Mitigate Unknown Biases with Debiasing Alternate NetworksCode1
Time Is MattEr: Temporal Self-supervision for Video TransformersCode1
Multi-manifold Attention for Vision Transformers0
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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