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
Motion meets Attention: Video Motion PromptsCode1
Motion Representation Using Residual Frames with 3D CNNCode1
Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the MotionCode1
Can An Image Classifier Suffice For Action Recognition?Code1
HierVL: Learning Hierarchical Video-Language EmbeddingsCode1
Generative Model-based Feature Knowledge Distillation for Action RecognitionCode1
Fusion-GCN: Multimodal Action Recognition using Graph Convolutional NetworksCode1
Gimme Signals: Discriminative signal encoding for multimodal activity recognitionCode1
Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed TransformerCode1
BASAR:Black-box Attack on Skeletal Action RecognitionCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action PredictionCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
Fisher Information guided Purification against Backdoor AttacksCode1
FLAVR: Flow-Agnostic Video Representations for Fast Frame InterpolationCode1
Federated Self-supervised Learning for Video UnderstandingCode1
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
Few-shot Action Recognition with Prototype-centered Attentive LearningCode1
Florence: A New Foundation Model for Computer VisionCode1
Grad-CAM++: Improved Visual Explanations for Deep Convolutional NetworksCode1
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
Multi-Granularity Hand Action DetectionCode1
Approximated Bilinear Modules for Temporal ModelingCode1
Actions as Moving PointsCode1
Fast Fourier ConvolutionCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
Benchmarking Micro-action Recognition: Dataset, Methods, and ApplicationsCode1
FreqMixFormerV2: Lightweight Frequency-aware Mixed Transformer for Human Skeleton Action RecognitionCode1
Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic ScenesCode1
A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion RecognitionCode1
GCN-DevLSTM: Path Development for Skeleton-Based Action RecognitionCode1
BEVT: BERT Pretraining of Video TransformersCode1
EZ-CLIP: Efficient Zeroshot Video Action RecognitionCode1
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
Exploring Few-Shot Adaptation for Activity Recognition on Diverse DomainsCode1
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action RecognitionCode1
ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and MoreCode1
Full-Body Articulated Human-Object InteractionCode1
Augmented Neural Fine-Tuning for Efficient Backdoor PurificationCode1
Anonymization for Skeleton 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