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 726750 of 2759 papers

TitleStatusHype
Domain and View-point Agnostic Hand Action RecognitionCode0
MetaVD: A Meta Video Dataset for enhancing human action recognition datasetsCode0
A Variational Graph Autoencoder for Manipulation Action Recognition and PredictionCode0
LSTA: Long Short-Term Attention for Egocentric Action RecognitionCode0
LSTA-Net: Long short-term Spatio-Temporal Aggregation Network for Skeleton-based Action RecognitionCode0
Low-light Environment Neural SurveillanceCode0
Long-term Temporal Convolutions for Action RecognitionCode0
Long-Term Feature Banks for Detailed Video UnderstandingCode0
LSFB-CONT and LSFB-ISOL: Two New Datasets for Vision-Based Sign Language RecognitionCode0
Local Spherical Harmonics Improve Skeleton-Based Hand Action RecognitionCode0
LoCATe-GAT: Modeling Multi-Scale Local Context and Action Relationships for Zero-Shot Action RecognitionCode0
Lightweight Recurrent Cross-modal Encoder for Video Question AnsweringCode0
ADG-Pose: Automated Dataset Generation for Real-World Human Pose EstimationCode0
AutoGCN -- Towards Generic Human Activity Recognition with Neural Architecture SearchCode0
Making Third Person Techniques Recognize First-Person Actions in Egocentric VideosCode0
DVANet: Disentangling View and Action Features for Multi-View Action RecognitionCode0
Learn to cycle: Time-consistent feature discovery for action recognitionCode0
Learning Visual Actions Using Multiple Verb-Only LabelsCode0
Learning with privileged information via adversarial discriminative modality distillationCode0
Let's Dance: Learning From Online Dance VideosCode0
MLP-3D: A MLP-like 3D Architecture with Grouped Time MixingCode0
Learning Video Representations from Correspondence ProposalsCode0
Learning to Estimate Pose by Watching VideosCode0
MMTM: Multimodal Transfer Module for CNN FusionCode0
Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity RecognitionCode0
Show:102550
← PrevPage 30 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