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 601625 of 2759 papers

TitleStatusHype
Multi-level Second-order Few-shot LearningCode0
Multimodal Attack Detection for Action Recognition ModelsCode0
Coarse or Fine? Recognising Action End States without LabelsCode0
Action Recognition Using Temporal Shift Module and Ensemble LearningCode0
CNN based Multistage Gated Average Fusion (MGAF) for Human Action Recognition Using Depth and Inertial SensorsCode0
Multi class activity classification in videos using Motion History Image generationCode0
Multi-attention Networks for Temporal Localization of Video-level LabelsCode0
Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image DatasetsCode0
An Animation-based Augmentation Approach for Action Recognition from Discontinuous VideoCode0
MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation LearningCode0
Moments in Time Dataset: one million videos for event understandingCode0
Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN FeaturesCode0
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal AggregationCode0
Modeling the Relative Visual Tempo for Self-supervised Skeleton-based Action RecognitionCode0
Modality Distillation with Multiple Stream Networks for Action RecognitionCode0
MaCLR: Motion-aware Contrastive Learning of Representations for VideosCode0
Class Feature Pyramids for Video ExplanationCode0
MMTM: Multimodal Transfer Module for CNN FusionCode0
MOFO: MOtion FOcused Self-Supervision for Video UnderstandingCode0
Analysis of Hand Segmentation in the WildCode0
MMG-Ego4D: Multimodal Generalization in Egocentric Action RecognitionCode0
Analysis and Extensions of Adversarial Training for Video ClassificationCode0
A Comparative Review of Recent Kinect-based Action Recognition AlgorithmsCode0
Analysis and Evaluation of Kinect-based Action Recognition AlgorithmsCode0
Mission Balance: Generating Under-represented Class Samples using Video Diffusion ModelsCode0
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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