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 276300 of 2759 papers

TitleStatusHype
Concatenated Masked Autoencoders as Spatial-Temporal LearnerCode1
Approximated Bilinear Modules for Temporal ModelingCode1
Actions as Moving PointsCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
ConvNet Architecture Search for Spatiotemporal Feature LearningCode1
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic ScenesCode1
CT-Net: Channel Tensorization Network for Video ClassificationCode1
D^2ST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action RecognitionCode1
DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action RecognitionCode1
Challenges in Video-Based Infant Action Recognition: A Critical Examination of the State of the ArtCode1
ARID: A New Dataset for Recognizing Action in the DarkCode1
AR-Net: Adaptive Frame Resolution for Efficient Action RecognitionCode1
ViViT: A Video Vision TransformerCode1
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action RecognitionCode1
ArtEmis: Affective Language for Visual ArtCode1
DEVIAS: Learning Disentangled Video Representations of Action and SceneCode1
DirecFormer: A Directed Attention in Transformer Approach to Robust Action RecognitionCode1
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
CAST: Cross-Attention in Space and Time for Video Action RecognitionCode1
Full-Body Articulated Human-Object InteractionCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
ActionCLIP: A New Paradigm for Video Action RecognitionCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
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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