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 351375 of 2759 papers

TitleStatusHype
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
Compressing Recurrent Neural Networks with Tensor Ring for Action RecognitionCode1
Concatenated Masked Autoencoders as Spatial-Temporal LearnerCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual ActionsCode1
Anonymization for Skeleton Action RecognitionCode1
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
KNN-MMD: Cross Domain Wireless Sensing via Local Distribution AlignmentCode1
Complex Sequential Understanding through the Awareness of Spatial and Temporal ConceptsCode1
Language Knowledge-Assisted Representation Learning for Skeleton-Based Action RecognitionCode1
ViNet: Pushing the limits of Visual Modality for Audio-Visual Saliency PredictionCode1
Large-Scale Video Classification with Convolutional Neural NetworksCode1
Volterra Neural Networks (VNNs)Code1
Learning Discriminative Representations for Skeleton Based Action RecognitionCode1
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action RecognitionCode1
BABEL: Bodies, Action and Behavior with English LabelsCode1
Counterfactual Debiasing Inference for Compositional Action RecognitionCode1
Learning Spatiotemporal Features via Video and Text Pair DiscriminationCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
Learning State-Aware Visual Representations from Audible InteractionsCode1
CLIP-guided Prototype Modulating for Few-shot Action RecognitionCode1
CIDEr: Consensus-based Image Description EvaluationCode1
CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual DistillationCode1
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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