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 326350 of 2759 papers

TitleStatusHype
Cross-Block Fine-Grained Semantic Cascade for Skeleton-Based Sports Action Recognition0
Enhancing Action Recognition from Low-Quality Skeleton Data via Part-Level Knowledge Distillation0
Learning Discriminative Spatio-temporal Representations for Semi-supervised Action Recognition0
An Improved Graph Pooling Network for Skeleton-Based Action Recognition0
HDBN: A Novel Hybrid Dual-branch Network for Robust Skeleton-based Action RecognitionCode1
Interactive Generation of Laparoscopic Videos with Diffusion Models0
DENOISER: Rethinking the Robustness for Open-Vocabulary Action Recognition0
Driver Activity Classification Using Generalizable Representations from Vision-Language Models0
Combating Missing Modalities in Egocentric Videos at Test Time0
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction AlignmentCode1
Attack on Scene Flow using Point CloudsCode0
Aligning Actions and Walking to LLM-Generated Textual DescriptionsCode0
Simultaneous Detection and Interaction Reasoning for Object-Centric Action Recognition0
VG4D: Vision-Language Model Goes 4D Video RecognitionCode1
Lower Limb Movements Recognition Based on Feature Recursive Elimination and Backpropagation Neural Network0
Learning to Score Sign Language with Two-stage Method0
HumMUSS: Human Motion Understanding using State Space Models0
MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognition0
Leveraging Temporal Contextualization for Video Action RecognitionCode2
A Survey on Multimodal Wearable Sensor-based Human Action Recognition0
In My Perspective, In My Hands: Accurate Egocentric 2D Hand Pose and Action RecognitionCode0
Multimodal Attack Detection for Action Recognition ModelsCode0
Exploring Explainability in Video Action Recognition0
MSSTNet: A Multi-Scale Spatio-Temporal CNN-Transformer Network for Dynamic Facial Expression Recognition0
Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition 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
4InternVideoTop-1 Accuracy77.2Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6Unverified
4VideoMAE V2-g3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified