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 9761000 of 2759 papers

TitleStatusHype
Adversarial Domain Adaptation for Action Recognition Around the Clock0
Dynamic Graph Modules for Modeling Object-Object Interactions in Activity Recognition0
fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs0
Collaborative Attention Mechanism for Multi-View Action Recognition0
Frame Order Matters: A Temporal Sequence-Aware Model for Few-Shot Action Recognition0
Free-Form Composition Networks for Egocentric Action Recognition0
Knowledge Distillation for Human Action Anticipation0
Frequency-aware Event Cloud Network0
HAUAR: Home Automation Using Action Recognition0
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks0
From CNNs to Transformers in Multimodal Human Action Recognition: A Survey0
From Detection to Action Recognition: An Edge-Based Pipeline for Robot Human Perception0
An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data0
From Image to Video: An Empirical Study of Diffusion Representations0
From Pose to Activity: Surveying Datasets and Introducing CONVERSE0
Dynamic Appearance: A Video Representation for Action Recognition with Joint Training0
Dynamically Encoded Actions Based on Spacetime Saliency0
Adversarial Cross-Domain Action Recognition with Co-Attention0
Dynamic Action Recognition: A convolutional neural network model for temporally organized joint location data0
Actionness Estimation Using Hybrid Fully Convolutional Networks0
DWnet: Deep-Wide Network for 3D Action Recognition0
FSD-10: A Dataset for Competitive Sports Content Analysis0
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition0
Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition0
Baby Physical Safety Monitoring in Smart Home Using Action Recognition System0
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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