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 11011125 of 2759 papers

TitleStatusHype
MMG-Ego4D: Multi-Modal Generalization in Egocentric Action RecognitionCode0
Few-shot Action Recognition via Intra- and Inter-Video Information Maximization0
Self-Supervised Video Representation Learning via Latent Time Navigation0
Learning Video-Conditioned Policies for Unseen Manipulation Tasks0
Building Neural Networks on Matrix Manifolds: A Gyrovector Space Approach0
Modelling Spatio-Temporal Interactions for Compositional Action Recognition0
Cross-Stream Contrastive Learning for Self-Supervised Skeleton-Based Action Recognition0
Cross-view Action Recognition via Contrastive View-invariant Representation0
Physical Adversarial Attacks for Surveillance: A Survey0
Deep Graph Reprogramming0
RHM: Robot House Multi-view Human Activity Recognition DatasetCode0
End-to-End Spatio-Temporal Action Localisation with Video Transformers0
Video-based Contrastive Learning on Decision Trees: from Action Recognition to Autism Diagnosis0
Search-Map-Search: A Frame Selection Paradigm for Action Recognition0
A baseline on continual learning methods for video action recognition0
Human activity recognition using deep learning approaches and single frame cnn and convolutional lstm0
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization0
GoferBot: A Visual Guided Human-Robot Collaborative Assembly System0
ATTACH Dataset: Annotated Two-Handed Assembly Actions for Human Action Understanding0
PMI Sampler: Patch Similarity Guided Frame Selection for Aerial Action RecognitionCode0
Skeleton-based action analysis for ADHD diagnosis0
NEV-NCD: Negative Learning, Entropy, and Variance regularization based novel action categories discoveryCode0
Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition0
Attack-Augmentation Mixing-Contrastive Skeletal Representation LearningCode0
Therbligs in Action: Video Understanding through Motion Primitives0
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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