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 1801–1850 of 2759 papers

TitleStatusHype
Dynamic Sampling Networks for Efficient Action Recognition in Videos—0
FBK-HUPBA Submission to the EPIC-Kitchens Action Recognition 2020 Challenge—0
Sequential Feature Filtering Classifier—0
A Real-time Action Representation with Temporal Encoding and Deep Compression—0
Learn to cycle: Time-consistent feature discovery for action recognitionCode0
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks—0
DTG-Net: Differentiated Teachers Guided Self-Supervised Video Action Recognition—0
3DFCNN: Real-Time Action Recognition using 3D Deep Neural Networks with Raw Depth Information—0
PNL: Efficient Long-Range Dependencies Extraction with Pyramid Non-Local Module for Action Recognition—0
Deep hierarchical pooling design for cross-granularity action recognition—0
Action Recognition with Deep Multiple Aggregation Networks—0
WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos—0
Regularization on Spatio-Temporally Smoothed Feature for Action Recognition—0
Context Aware Graph Convolution for Skeleton-Based Action Recognition—0
Action Genome: Actions As Compositions of Spatio-Temporal Scene Graphs—0
In the Eye of the Beholder: Gaze and Actions in First Person Video—0
Unifying Few- and Zero-Shot Egocentric Action Recognition—0
Invariant 3D Shape Recognition using Predictive Modular Neural Networks—0
SpotFast Networks with Memory Augmented Lateral Transformers for LipreadingCode0
Intra- and Inter-Action Understanding via Temporal Action Parsing—0
Discriminative Dictionary Design for Action Classification in Still Images and Videos—0
Retrieving and Highlighting Action with Spatiotemporal Reference—0
Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation—0
CoSimGNN: Towards Large-scale Graph Similarity Computation—0
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition—0
Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events—0
Exploiting Inter-Frame Regional Correlation for Efficient Action Recognition—0
Streaming Object Detection for 3-D Point Clouds—0
A Semantics-Guided Graph Convolutional Network for Skeleton-Based Action Recognition—0
Inferring Temporal Compositions of Actions Using Probabilistic Automata—0
HAPRec: Hybrid Activity and Plan Recognizer—0
Can We Learn Heuristics For Graphical Model Inference Using Reinforcement Learning?—0
Human and Machine Action Prediction Independent of Object Information—0
Action recognition in real-world videos—0
TAEN: Temporal Aware Embedding Network for Few-Shot Action Recognition—0
Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition—0
Combining Deep Learning Classifiers for 3D Action Recognition—0
FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding—0
Spatiotemporal Fusion in 3D CNNs: A Probabilistic View—0
ASL Recognition with Metric-Learning based Lightweight Network—0
What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition—0
Human action recognition with a large-scale brain-inspired photonic computer—0
Knowing What, Where and When to Look: Efficient Video Action Modeling with Attention—0
Speech2Action: Cross-modal Supervision for Action Recognition—0
Action Localization through Continual Predictive Learning—0
Modeling Cross-view Interaction Consistency for Paired Egocentric Interaction Recognition—0
Ensembles of Deep Neural Networks for Action Recognition in Still Images—0
Temporal Extension Module for Skeleton-Based Action Recognition—0
STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition—0
Feedback Graph Convolutional Network for Skeleton-based Action Recognition—0
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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
2OmniVec23-fold Accuracy99.6—Unverified
3OmniVec3-fold Accuracy99.6—Unverified
4VideoMAE V2-g3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
10Text4Vis3-fold Accuracy98.2—Unverified