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 551575 of 2759 papers

TitleStatusHype
ConvNet Architecture Search for Spatiotemporal Feature LearningCode1
Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action RecognitionCode1
Decoupling GCN with DropGraph Module for Skeleton-Based Action RecognitionCode1
MoViNets: Mobile Video Networks for Efficient Video RecognitionCode1
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
Approximated Bilinear Modules for Temporal ModelingCode1
Actions as Moving PointsCode1
Dynamic Perceiver for Efficient Visual RecognitionCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the BackboneCode1
Part-aware Unified Representation of Language and Skeleton for Zero-shot Action RecognitionCode1
Play Fair: Frame Attributions in Video ModelsCode1
PREDICT & CLUSTER: Unsupervised Skeleton Based Action RecognitionCode1
Counterfactual Debiasing Inference for Compositional Action RecognitionCode1
Multi-dataset Training of Transformers for Robust Action RecognitionCode1
PREGO: online mistake detection in PRocedural EGOcentric videosCode1
Multiscale Vision TransformersCode1
EgoAdapt: A multi-stream evaluation study of adaptation to real-world egocentric user videoCode1
Cross-Architecture Self-supervised Video Representation LearningCode1
EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal TokensCode1
EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery VideosCode1
PSTNet: Point Spatio-Temporal Convolution on Point Cloud SequencesCode1
VSViG: Real-time Video-based Seizure Detection via Skeleton-based Spatiotemporal ViGCode1
EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity UnderstandingCode1
YouTube-8M: A Large-Scale Video Classification BenchmarkCode1
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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