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 26262650 of 2759 papers

TitleStatusHype
Dynamic Image Networks for Action RecognitionCode0
VidConv: A modernized 2D ConvNet for Efficient Video RecognitionCode0
Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingCode0
Improving Skeleton-based Action Recognition with Interactive Object InformationCode0
2D Pose Estimation based Child Action RecognitionCode0
Audio-Visual Model Distillation Using Acoustic ImagesCode0
Resource Efficient 3D Convolutional Neural NetworksCode0
ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action RecognitionCode0
Support Vector Machines with Time Series Distance Kernels for Action ClassificationCode0
Im2Flow: Motion Hallucination from Static Images for Action RecognitionCode0
I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge GraphsCode0
DVANet: Disentangling View and Action Features for Multi-View Action RecognitionCode0
Video Action Recognition Collaborative Learning with Dynamics via PSO-ConvNet TransformerCode0
View-Invariant, Occlusion-Robust Probabilistic Embedding for Human PoseCode0
Idempotent Unsupervised Representation Learning for Skeleton-Based Action RecognitionCode0
Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video ClassificationCode0
Attentive Semantic Video Generation using CaptionsCode0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
Rethinking Zero-shot Action Recognition: Learning from Latent Atomic ActionsCode0
View-Invariant Probabilistic Embedding for Human PoseCode0
I3D-LSTM: A New Model for Human Action RecognitionCode0
Human activity recognition from skeleton posesCode0
Human Action Recognition Using Deep Multilevel Multimodal (M2) Fusion of Depth and Inertial SensorsCode0
Win-Fail Action RecognitionCode0
Review of Action Recognition and Detection MethodsCode0
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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