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 276300 of 2759 papers

TitleStatusHype
MILES: Visual BERT Pre-training with Injected Language Semantics for Video-text RetrievalCode1
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
Temporal Alignment Networks for Long-term VideoCode1
TALLFormer: Temporal Action Localization with a Long-memory TransformerCode1
Stochastic Backpropagation: A Memory Efficient Strategy for Training Video ModelsCode1
SPAct: Self-supervised Privacy Preservation for Action RecognitionCode1
Continual Spatio-Temporal Graph Convolutional NetworksCode1
DirecFormer: A Directed Attention in Transformer Approach to Robust Action RecognitionCode1
Group Contextualization for Video RecognitionCode1
Source-free Video Domain Adaptation by Learning Temporal Consistency for Action RecognitionCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
Motion-driven Visual Tempo Learning for Video-based Action RecognitionCode1
Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse OcclusionsCode1
Student Dangerous Behavior Detection in SchoolCode1
Source-Free Progressive Graph Learning for Open-Set Domain AdaptationCode1
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensorsCode1
MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video RecognitionCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
TSA-Net: Tube Self-Attention Network for Action Quality AssessmentCode1
Spatio-Temporal Tuples Transformer for Skeleton-Based Action RecognitionCode1
E2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action RecognitionCode1
InfoGCN: Representation Learning for Human Skeleton-Based Action RecognitionCode1
Tell me what you see: A zero-shot action recognition method based on natural language descriptionsCode1
Masked Feature Prediction for Self-Supervised Visual Pre-TrainingCode1
SVIP: Sequence VerIfication for Procedures in VideosCode1
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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