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 1151–1200 of 2759 papers

TitleStatusHype
Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition—0
MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action RecognitionCode0
Ego-Vehicle Action Recognition based on Semi-Supervised Contrastive Learning—0
AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoning—0
Texture-Based Input Feature Selection for Action Recognition—0
Open Set Action Recognition via Multi-Label Evidential Learning—0
Spatial-temporal Transformer-guided Diffusion based Data Augmentation for Efficient Skeleton-based Action Recognition—0
Temporal-Channel Topology Enhanced Network for Skeleton-Based Action RecognitionCode0
DMMG: Dual Min-Max Games for Self-Supervised Skeleton-Based Action Recognition—0
Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms—0
Multi-scale Motion-Aware Module for Video Action Recognition—0
Table Tennis Stroke Detection and Recognition Using Ball Trajectory Data—0
Video Action Recognition Collaborative Learning with Dynamics via PSO-ConvNet TransformerCode0
Dynamic Spatial-temporal Hypergraph Convolutional Network for Skeleton-based Action Recognition—0
Audio-Visual Contrastive Learning with Temporal Self-Supervision—0
Fine-grained Affordance Annotation for Egocentric Hand-Object Interaction VideosCode0
Spatiotemporal Decouple-and-Squeeze Contrastive Learning for Semi-Supervised Skeleton-based Action Recognition—0
Pyramid Self-attention Polymerization Learning for Semi-supervised Skeleton-based Action RecognitionCode0
Skeleton-based Human Action Recognition via Convolutional Neural Networks (CNN)—0
Action Capsules: Human Skeleton Action Recognition—0
Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2022—0
Skeleton-based Action Recognition through Contrasting Two-Stream Spatial-Temporal Networks—0
Improving Zero-Shot Action Recognition using Human Instruction with Text Description—0
Revisiting the Spatial and Temporal Modeling for Few-shot Action Recognition—0
CNN-Based Action Recognition and Pose Estimation for Classifying Animal Behavior from Videos: A Survey—0
CMAE-V: Contrastive Masked Autoencoders for Video Action Recognition—0
Deep learning-based approaches for human motion decoding in smart walkers for rehabilitation—0
Simplifying Open-Set Video Domain Adaptation with Contrastive LearningCode0
STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition—0
Look, Listen, and Attack: Backdoor Attacks Against Video Action Recognition—0
Multi-View Action Recognition Using Contrastive LearningCode0
Ego-Only: Egocentric Action Detection without Exocentric Transferring—0
Efficient Robustness Assessment via Adversarial Spatial-Temporal Focus on VideosCode0
SkeleTR: Towards Skeleton-based Action Recognition in the Wild—0
Modeling the Relative Visual Tempo for Self-supervised Skeleton-based Action RecognitionCode0
ReGen: A good Generative Zero-Shot Video Classifier Should be Rewarded—0
A Large-Scale Robustness Analysis of Video Action Recognition Models—0
LoTE-Animal: A Long Time-span Dataset for Endangered Animal Behavior Understanding—0
Active Exploration of Multimodal Complementarity for Few-Shot Action Recognition—0
Leveraging Temporal Context in Low Representational Power Regimes—0
Hierarchical Explanations for Video Action RecognitionCode0
Unified Pose Sequence Modeling—0
Growing a Brain with Sparsity-Inducing Generation for Continual LearningCode0
MMG-Ego4D: Multimodal Generalization in Egocentric Action RecognitionCode0
Parallel Attention Interaction Network for Few-Shot Skeleton-Based Action Recognition—0
Transformers in Action Recognition: A Review on Temporal Modeling—0
Adaptive frame selection in two dimensional convolutional neural network action recognitionCode0
SMAM: Self and Mutual Adaptive Matching for Skeleton-Based Few-Shot Action Recognition—0
From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive HydronephrosisCode0
Understanding Ethics, Privacy, and Regulations in Smart Video Surveillance for Public Safety—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