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

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Showing 351–400 of 2759 papers

TitleStatusHype
Home Action Genome: Cooperative Compositional Action UnderstandingCode1
Full-Body Articulated Human-Object InteractionCode1
Elaborative Rehearsal for Zero-shot Action RecognitionCode1
Mitigating and Evaluating Static Bias of Action Representations in the Background and the ForegroundCode1
EgoAdapt: A multi-stream evaluation study of adaptation to real-world egocentric user videoCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual ActionsCode1
EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal TokensCode1
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the BackboneCode1
AViD Dataset: Anonymized Videos from Diverse CountriesCode1
Motion Representation Using Residual Frames with 3D CNNCode1
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action RecognitionCode1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D NetworksCode1
CAST: Cross-Attention in Space and Time for Video Action RecognitionCode1
EgoNCE++: Do Egocentric Video-Language Models Really Understand Hand-Object Interactions?Code1
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action RecognitionCode1
BABEL: Bodies, Action and Behavior with English LabelsCode1
Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven ReasoningCode1
MSAF: Multimodal Split Attention FusionCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
End-to-End Learning of Visual Representations from Uncurated Instructional VideosCode1
End-to-End Streaming Video Temporal Action Segmentation with Reinforce LearningCode1
Multi-Modal Domain Adaptation for Fine-Grained Action RecognitionCode1
ACTION-Net: Multipath Excitation for Action RecognitionCode1
Enlarging Instance-specific and Class-specific Information for Open-set Action RecognitionCode1
Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the MotionCode1
BASAR:Black-box Attack on Skeletal Action RecognitionCode1
Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action RecognitionCode1
Multivariate LSTM-FCNs for Time Series ClassificationCode1
EPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language modelsCode1
EPAM-Net: An Efficient Pose-driven Attention-guided Multimodal Network for Video Action RecognitionCode1
3D CNNs with Adaptive Temporal Feature ResolutionsCode1
Benchmarking Micro-action Recognition: Dataset, Methods, and ApplicationsCode1
EventRPG: Event Data Augmentation with Relevance Propagation GuidanceCode1
Anonymization for Skeleton Action RecognitionCode1
Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and DataCode1
BEVT: BERT Pretraining of Video TransformersCode1
Evidential Deep Learning for Open Set Action RecognitionCode1
ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and MoreCode1
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action RecognitionCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
Human-centric Scene Understanding for 3D Large-scale ScenariosCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
EZ-CLIP: Efficient Zeroshot Video Action RecognitionCode1
Feature Combination Meets Attention: Baidu Soccer Embeddings and Transformer based Temporal DetectionCode1
Fast Fourier ConvolutionCode1
Exploring Few-Shot Adaptation for Activity Recognition on Diverse DomainsCode1
Federated Self-supervised Learning for Video UnderstandingCode1
Bringing Online Egocentric Action Recognition into the wildCode1
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All datasetsSomething-Something V2UCF101HMDB-51Something-Something V1AVA v2.2EPIC-KITCHENS-100NTU RGB+DNTU RGB+D 120Diving-48ActivityNetAVA v2.1H2O (2 Hands and Objects)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4—Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1—Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3—Unverified
4InternVideoTop-1 Accuracy77.2—Unverified
5DejaVidTop-1 Accuracy77.2—Unverified
6InternVideo2-1BTop-1 Accuracy77.1—Unverified
7VideoMAE V2-gTop-1 Accuracy77—Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7—Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5—Unverified
10TubeViT-LTop-1 Accuracy76.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7—Unverified
2OmniVec3-fold Accuracy99.6—Unverified
3VideoMAE V2-g3-fold Accuracy99.6—Unverified
4OmniVec23-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
9OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
10Text4Vis3-fold Accuracy98.2—Unverified