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 576600 of 2759 papers

TitleStatusHype
IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in VideosCode1
ARID: A New Dataset for Recognizing Action in the DarkCode1
Integrating Human Parsing and Pose Network for Human Action RecognitionCode1
Composable Augmentation Encoding for Video Representation Learning0
Complex Video Action Reasoning via Learnable Markov Logic Network0
Complex Human Action Recognition in Live Videos Using Hybrid FR-DL Method0
Ani-GIFs: A benchmark dataset for domain generalization of action recognition from GIFs0
Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion0
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark0
Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions0
Action Recognition via Pose-Based Graph Convolutional Networks with Intermediate Dense Supervision0
ActAR: Actor-Driven Pose Embeddings for Video Action Recognition0
A New Representation of Skeleton Sequences for 3D Action Recognition0
Distributed non-parametric deep and wide networks0
Distribution of Action Movements (DAM): A Descriptor for Human Action Recognition0
CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices0
Combining Spatio-Temporal Appearance Descriptors and Optical Flow for Human Action Recognition in Video Data0
A New Adjacency Matrix Configuration in GCN-based Models for Skeleton-based Action Recognition0
Combining Deep Learning Classifiers for 3D Action Recognition0
Combining ConvNets with Hand-Crafted Features for Action Recognition Based on an HMM-SVM Classifier0
A New Action Recognition Framework for Video Highlights Summarization in Sporting Events0
Action Recognition Utilizing YGAR Dataset0
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition0
Combating Missing Modalities in Egocentric Videos at Test Time0
Colo-SCRL: Self-Supervised Contrastive Representation Learning for Colonoscopic Video Retrieval0
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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