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 17511775 of 2759 papers

TitleStatusHype
Towards Improved Human Action Recognition Using Convolutional Neural Networks and Multimodal Fusion of Depth and Inertial Sensor Data0
Multidomain Multimodal Fusion For Human Action Recognition Using Inertial Sensors0
Object Properties Inferring from and Transfer for Human Interaction Motions0
Accuracy and Performance Comparison of Video Action Recognition Approaches0
ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome PredictionCode0
Look, Listen, and Attend: Co-Attention Network for Self-Supervised Audio-Visual Representation Learning0
2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework0
Richly Activated Graph Convolutional Network for Robust Skeleton-based Action RecognitionCode0
Exploring Relations in Untrimmed Videos for Self-Supervised Learning0
Residual Frames with Efficient Pseudo-3D CNN for Human Action Recognition0
Recognition and 3D Localization of Pedestrian Actions from Monocular Video0
Vision and Inertial Sensing Fusion for Human Action Recognition : A Review0
Learning Video Representations by Transforming Time0
Shuffle and Attend: Video Domain Adaptation0
Towards Efficient Coarse-to-Fine Networks for Action and Gesture Recognition0
Learning Actionness via Long-range Temporal Order Verification0
Improving Skeleton-based Action Recognitionwith Robust Spatial and Temporal Features0
Self-supervised Motion Representation via Scattering Local Motion Cues0
On Dropping Clusters to Regularize Graph Convolutional Neural Networks0
CoTeRe-Net: Discovering Collaborative Ternary Relations in VideosCode0
A Recurrent Transformer Network for Novel View Action SynthesisCode0
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition0
Hierarchical Action Classification with Network Pruning0
Learning Video Representations from Textual Web Supervision0
On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures0
Show:102550
← PrevPage 71 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