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 22012225 of 2759 papers

TitleStatusHype
O-TALC: Steps Towards Combating Oversegmentation within Online Action Segmentation0
OwlSight: A Robust Illumination Adaptation Framework for Dark Video Human Action Recognition0
PA3D: Pose-Action 3D Machine for Video Recognition0
Pairwise Linear Regression Classification for Image Set Retrieval0
Parallel Attention Interaction Network for Few-Shot Skeleton-Based Action Recognition0
Parallel Separable 3D Convolution for Video and Volumetric Data Understanding0
Part-aware Prototypical Graph Network for One-shot Skeleton-based Action Recognition0
Part-level Action Parsing via a Pose-guided Coarse-to-Fine Framework0
Path-adaptive Spatio-Temporal State Space Model for Event-based Recognition with Arbitrary Duration0
Attention Distillation for Learning Video Representations0
PBADet: A One-Stage Anchor-Free Approach for Part-Body Association0
PCBEAR: Pose Concept Bottleneck for Explainable Action Recognition0
P-CNN: Pose-based CNN Features for Action Recognition0
Pedestrian Crossing Action Recognition and Trajectory Prediction with 3D Human Keypoints0
Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition0
PERF-Net: Pose Empowered RGB-Flow Net0
Per-Sample Kernel Adaptation for Visual Recognition and Grouping0
Persistent Homology of Attractors For Action Recognition0
PeVL: Pose-Enhanced Vision-Language Model for Fine-Grained Human Action Recognition0
PGCN-TCA: Pseudo Graph Convolutional Network With Temporal and Channel-Wise Attention for Skeleton-Based Action Recognition0
Phase Space Reconstruction Network for Lane Intrusion Action Recognition0
Physical Adversarial Attacks for Surveillance: A Survey0
PhysPT: Physics-aware Pretrained Transformer for Estimating Human Dynamics from Monocular Videos0
Pillar Networks++: Distributed non-parametric deep and wide networks0
PKU-MMD: A Large Scale Benchmark for Continuous Multi-Modal Human Action Understanding0
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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