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 18761900 of 2759 papers

TitleStatusHype
Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences0
Human Action Performance using Deep Neuro-Fuzzy Recurrent Attention Model0
Action Recognition and State Change Prediction in a Recipe Understanding Task Using a Lightweight Neural Network Model0
Zero-Shot Activity Recognition with Videos0
Context-Aware Cross-Attention for Skeleton-Based Human Action Recognition0
MixTConv: Mixed Temporal Convolutional Kernels for Efficient Action Recogntion0
Recognizing Video Events with Varying RhythmsCode0
Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors0
Few-shot Action Recognition with Permutation-invariant AttentionCode0
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal0
PGCN-TCA: Pseudo Graph Convolutional Network With Temporal and Channel-Wise Attention for Skeleton-Based Action Recognition0
Human Action Recognition and Assessment via Deep Neural Network Self-Organization0
Focusing and Diffusion: Bidirectional Attentive Graph Convolutional Networks for Skeleton-based Action Recognition0
DMCL: Distillation Multiple Choice Learning for Multimodal Action RecognitionCode0
Adversarial Cross-Domain Action Recognition with Co-Attention0
Something-Else: Compositional Action Recognition with Spatial-Temporal Interaction NetworksCode0
Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatial-Temporal Graph Convolutional Network for Action Recognition0
Self-Attention Network for Skeleton-based Human Action Recognition0
Mimetics: Towards Understanding Human Actions Out of Context0
Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional NetworksCode0
Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action RecognitionCode0
SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong0
Totally Deep Support Vector Machines0
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action RecognitionCode0
Hidden Markov Model: Tutorial0
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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