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 101150 of 2759 papers

TitleStatusHype
A Body Part Embedding Model With Datasets for Measuring 2D Human Motion SimilarityCode1
Augmented Neural Fine-Tuning for Efficient Backdoor PurificationCode1
Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action RecognitionCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual ActionsCode1
DSANet: Dynamic Segment Aggregation Network for Video-Level Representation LearningCode1
AViD Dataset: Anonymized Videos from Diverse CountriesCode1
ViNet: Pushing the limits of Visual Modality for Audio-Visual Saliency PredictionCode1
A Closer Look at Spatiotemporal Convolutions for Action RecognitionCode1
Decoupling GCN with DropGraph Module for Skeleton-Based Action RecognitionCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
BABEL: Bodies, Action and Behavior with English LabelsCode1
Data Efficient Video Transformer for Violence DetectionCode1
EAN: Event Adaptive Network for Enhanced Action RecognitionCode1
Action knowledge for video captioning with graph neural networksCode1
Benchmarking Micro-action Recognition: Dataset, Methods, and ApplicationsCode1
DDGCN: A Dynamic Directed Graph Convolutional Network for Action RecognitionCode1
BEVT: BERT Pretraining of Video TransformersCode1
Deep Analysis of CNN-based Spatio-temporal Representations for Action RecognitionCode1
DirecFormer: A Directed Attention in Transformer Approach to Robust Action RecognitionCode1
3D Human Action Representation Learning via Cross-View Consistency PursuitCode1
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion PerceptionCode1
BMN: Boundary-Matching Network for Temporal Action Proposal GenerationCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
Elaborative Rehearsal for Zero-shot Action RecognitionCode1
Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven ReasoningCode1
AR-Net: Adaptive Frame Resolution for Efficient Action RecognitionCode1
ARID: A New Dataset for Recognizing Action in the DarkCode1
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensorsCode1
Approximated Bilinear Modules for Temporal ModelingCode1
3DYoga90: A Hierarchical Video Dataset for Yoga Pose UnderstandingCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
D^2ST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action RecognitionCode1
Action Genome: Actions as Composition of Spatio-temporal Scene GraphsCode1
3DV: 3D Dynamic Voxel for Action Recognition in Depth VideoCode1
Anonymization for Skeleton Action RecognitionCode1
ArtEmis: Affective Language for Visual ArtCode1
Attention-Based Context Aware Reasoning for Situation RecognitionCode1
CT-Net: Channel Tensorization Network for Video ClassificationCode1
DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action RecognitionCode1
Discover and Mitigate Unknown Biases with Debiasing Alternate NetworksCode1
An Evaluation of Action Recognition Models on EPIC-KitchensCode1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
ConvNet Architecture Search for Spatiotemporal Feature LearningCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
Can An Image Classifier Suffice For Action Recognition?Code1
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
ActionCLIP: A New Paradigm for Video Action RecognitionCode1
Conquering the cnn over-parameterization dilemma: A volterra filtering approach for 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