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 25762600 of 2759 papers

TitleStatusHype
Modelling Temporal Information Using Discrete Fourier Transform for Video Classification0
Persistent Homology of Attractors For Action Recognition0
Learning zeroth class dictionary for human action recognition0
Pose for Action - Action for Pose0
Support Vector Machines with Time Series Distance Kernels for Action ClassificationCode0
Robust Multi-body Feature Tracker: A Segmentation-free Approach0
Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation0
Joint Recognition and Segmentation of Actions via Probabilistic Integration of Spatio-Temporal Fisher Vectors0
Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions0
Learning a Deep Model for Human Action Recognition from Novel Viewpoints0
Combining ConvNets with Hand-Crafted Features for Action Recognition Based on an HMM-SVM Classifier0
Order-aware Convolutional Pooling for Video Based Action Recognition0
RGB-D-based Action Recognition Datasets: A Survey0
Face-space Action Recognition by Face-Object Interactions0
Convolutional Architecture Exploration for Action Recognition and Image Classification0
Do Less and Achieve More: Training CNNs for Action Recognition Utilizing Action Images from the Web0
Harnessing the Deep Net Object Models for Enhancing Human Action Recognition0
Origami: A 803 GOp/s/W Convolutional Network Accelerator0
Action Recognition with Image Based CNN Features0
RNN Fisher Vectors for Action Recognition and Image Annotation0
Explaining NonLinear Classification Decisions with Deep Taylor DecompositionCode0
Moving poselets: A discriminative and interpretable skeletal motion representation for action recognition0
Rank Pooling for Action RecognitionCode0
Actions ~ TransformationsCode0
Category-Blind Human Action Recognition: A Practical Recognition System0
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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