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 26262650 of 2759 papers

TitleStatusHype
Learning Representations from Audio-Visual Spatial Alignment0
Learning Representative Temporal Features for Action Recognition0
Learning Scene Flow With Skeleton Guidance For 3D Action Recognition0
Learning Shape-Motion Representations from Geometric Algebra Spatio-Temporal Model for Skeleton-Based Action Recognition0
Learning Spatiotemporal Features for Infrared Action Recognition with 3D Convolutional Neural Networks0
Learning spatio-temporal representations with temporal squeeze pooling0
Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision0
Learning to Generalize without Bias for Open-Vocabulary Action Recognition0
Learning to Learn from Noisy Web Videos0
Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks0
Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model0
Learning to Recognize Actions on Objects in Egocentric Video with Attention Dictionaries0
Learning to Score Sign Language with Two-stage Method0
Learning to Sort Image Sequences via Accumulated Temporal Differences0
Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision0
Learning Using Privileged Information for Zero-Shot Action Recognition0
Learning Video-Conditioned Policies for Unseen Manipulation Tasks0
Learning Video Representations by Transforming Time0
Learning Video Representations from Textual Web Supervision0
Learning Video Representations of Human Motion From Synthetic Data0
Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization0
Learning Visual Affordance Grounding from Demonstration Videos0
Learning Visual Representation from Human Interactions0
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition0
Learning zeroth class dictionary for human action recognition0
Show:102550
← PrevPage 106 of 111Next →

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