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 10511075 of 2759 papers

TitleStatusHype
ActAR: Actor-Driven Pose Embeddings for Video Action Recognition0
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
Invisible-to-Visible: Privacy-Aware Human Instance Segmentation using Airborne Ultrasound via Collaborative Learning Variational Autoencoder0
Model-agnostic Multi-Domain Learning with Domain-Specific Adapters for Action Recognition0
3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition0
Towards End-to-End Integration of Dialog History for Improved Spoken Language Understanding0
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates0
SOS! Self-supervised Learning Over Sets Of Handled Objects In Egocentric Action Recognition0
Probabilistic Representations for Video Contrastive Learning0
Frequency Selective Augmentation for Video Representation Learning0
Hierarchical Self-supervised Representation Learning for Movie Understanding0
MM-SEAL: A Large-scale Video Dataset of Multi-person Multi-grained Spatio-temporally Action Localization0
Temporal Alignment Networks for Long-term VideoCode1
OccamNets: Mitigating Dataset Bias by Favoring Simpler HypothesesCode0
TALLFormer: Temporal Action Localization with a Long-memory TransformerCode1
Direct Dense Pose Estimation0
ObjectMix: Data Augmentation by Copy-Pasting Objects in Videos for Action Recognition0
Vision Transformer with Cross-attention by Temporal Shift for Efficient Action Recognition0
Stochastic Backpropagation: A Memory Efficient Strategy for Training Video ModelsCode1
SpatioTemporal Focus for Skeleton-based Action Recognition0
Controllable Augmentations for Video Representation Learning0
CycDA: Unsupervised Cycle Domain Adaptation from Image to VideoCode0
SPAct: Self-supervised Privacy Preservation for Action RecognitionCode1
Rethinking Zero-shot Action Recognition: Learning from Latent Atomic ActionsCode0
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural ActivitiesCode0
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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