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 16261650 of 2759 papers

TitleStatusHype
Exploring Relations in Untrimmed Videos for Self-Supervised Learning0
Self-supervised Temporal Discriminative Learning for Video Representation LearningCode1
Self-supervised learning using consistency regularization of spatio-temporal data augmentation for action recognitionCode1
Graph Convolution with Low-rank Learnable Local FiltersCode1
Late Temporal Modeling in 3D CNN Architectures with BERT for Action RecognitionCode1
Recognition and 3D Localization of Pedestrian Actions from Monocular Video0
RareAct: A video dataset of unusual interactionsCode1
Memory-augmented Dense Predictive Coding for Video Representation LearningCode1
SeCo: Exploring Sequence Supervision for Unsupervised Representation LearningCode1
Residual Frames with Efficient Pseudo-3D CNN for Human Action Recognition0
Vision and Inertial Sensing Fusion for Human Action Recognition : A Review0
Weight Excitation: Built-in Attention Mechanisms in Convolutional Neural NetworksCode1
Learning Actionness via Long-range Temporal Order Verification0
Towards Efficient Coarse-to-Fine Networks for Action and Gesture Recognition0
Decoupling GCN with DropGraph Module for Skeleton-Based Action RecognitionCode1
A Recurrent Transformer Network for Novel View Action SynthesisCode0
Multi-view Action Recognition using Cross-view Video PredictionCode1
Learning Video Representations by Transforming Time0
RubiksNet: Learnable 3D-Shift for Efficient Video Action RecognitionCode1
CoTeRe-Net: Discovering Collaborative Ternary Relations in VideosCode0
DDGCN: A Dynamic Directed Graph Convolutional Network for Action RecognitionCode1
On Dropping Clusters to Regularize Graph Convolutional Neural Networks0
Shuffle and Attend: Video Domain Adaptation0
Self-supervised Motion Representation via Scattering Local Motion Cues0
Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action RecognitionCode1
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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