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 251300 of 2759 papers

TitleStatusHype
EPAM-Net: An Efficient Pose-driven Attention-guided Multimodal Network for Video Action RecognitionCode1
Epic-Sounds: A Large-scale Dataset of Actions That SoundCode1
EPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language modelsCode1
Can An Image Classifier Suffice For Action Recognition?Code1
HierVL: Learning Hierarchical Video-Language EmbeddingsCode1
GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action PredictionCode1
Generative Model-based Feature Knowledge Distillation for Action RecognitionCode1
Grad-CAM++: Improved Visual Explanations for Deep Convolutional NetworksCode1
Benchmarking Micro-action Recognition: Dataset, Methods, and ApplicationsCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
Fusion-GCN: Multimodal Action Recognition using Graph Convolutional NetworksCode1
Graph Contrastive Learning for Skeleton-based Action RecognitionCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
Florence: A New Foundation Model for Computer VisionCode1
FreqMixFormerV2: Lightweight Frequency-aware Mixed Transformer for Human Skeleton Action RecognitionCode1
Multi-Granularity Hand Action DetectionCode1
ViNet: Pushing the limits of Visual Modality for Audio-Visual Saliency PredictionCode1
3DInAction: Understanding Human Actions in 3D Point CloudsCode1
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action RecognitionCode1
Fisher Information guided Purification against Backdoor AttacksCode1
Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed TransformerCode1
Graph in Graph Neural NetworkCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual ActionsCode1
BABEL: Bodies, Action and Behavior with English LabelsCode1
FLAVR: Flow-Agnostic Video Representations for Fast Frame InterpolationCode1
Approximated Bilinear Modules for Temporal ModelingCode1
Actions as Moving PointsCode1
Feature Combination Meets Attention: Baidu Soccer Embeddings and Transformer based Temporal DetectionCode1
BASAR:Black-box Attack on Skeletal Action RecognitionCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion RecognitionCode1
Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic ScenesCode1
GCN-DevLSTM: Path Development for Skeleton-Based Action RecognitionCode1
Gimme Signals: Discriminative signal encoding for multimodal activity recognitionCode1
BEVT: BERT Pretraining of Video TransformersCode1
Exploring Few-Shot Adaptation for Activity Recognition on Diverse DomainsCode1
ARID: A New Dataset for Recognizing Action in the DarkCode1
AR-Net: Adaptive Frame Resolution for Efficient Action RecognitionCode1
ViViT: A Video Vision TransformerCode1
Building a Multi-modal Spatiotemporal Expert for Zero-shot Action Recognition with CLIPCode1
ArtEmis: Affective Language for Visual ArtCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
Bringing Online Egocentric Action Recognition into the wildCode1
Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular DiseaseCode1
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action RecognitionCode1
Explore Human Parsing Modality for Action RecognitionCode1
CAST: Cross-Attention in Space and Time for Video Action RecognitionCode1
Augmented Neural Fine-Tuning for Efficient Backdoor PurificationCode1
EZ-CLIP: Efficient Zeroshot Video 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
4InternVideoTop-1 Accuracy77.2Unverified
5DejaVidTop-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
2OmniVec3-fold Accuracy99.6Unverified
3VideoMAE V2-g3-fold Accuracy99.6Unverified
4OmniVec23-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
9OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified