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 901925 of 2759 papers

TitleStatusHype
ActNetFormer: Transformer-ResNet Hybrid Method for Semi-Supervised Action Recognition in VideosCode0
Investigation of Different Skeleton Features for CNN-based 3D Action RecognitionCode0
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer VisionCode0
Learning Spatio-Temporal Features with 3D Residual Networks for Action RecognitionCode0
ActivityNet: A Large-Scale Video Benchmark for Human Activity UnderstandingCode0
Interaction Relational Network for Mutual Action RecognitionCode0
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural ActivitiesCode0
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video ArchitecturesCode0
In My Perspective, In My Hands: Accurate Egocentric 2D Hand Pose and Action RecognitionCode0
D3D: Distilled 3D Networks for Video Action RecognitionCode0
CycleACR: Cycle Modeling of Actor-Context Relations for Video Action DetectionCode0
CycDA: Unsupervised Cycle Domain Adaptation from Image to VideoCode0
Improving Skeleton-based Action Recognition with Interactive Object InformationCode0
3D Pose from Motion for Cross-view Action Recognition via Non-linear Circulant Temporal EncodingCode0
Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingCode0
Idempotent Unsupervised Representation Learning for Skeleton-Based Action RecognitionCode0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge GraphsCode0
I3D-LSTM: A New Model for Human Action RecognitionCode0
Im2Flow: Motion Hallucination from Static Images for Action RecognitionCode0
Human activity recognition from skeleton posesCode0
Human Action Recognition Using Deep Multilevel Multimodal (M2) Fusion of Depth and Inertial SensorsCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Features Understanding in 3D CNNs for Actions Recognition in VideoCode0
HPERL: 3D Human Pose Estimation from RGB and LiDARCode0
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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