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 10011025 of 2759 papers

TitleStatusHype
Language as the Medium: Multimodal Video Classification through text only0
Selective Volume Mixup for Video Action RecognitionCode0
Towards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention0
CaSAR: Contact-aware Skeletal Action Recognition0
hear-your-action: human action recognition by ultrasound active sensing0
TransNet: A Transfer Learning-Based Network for Human Action Recognition0
Grounded Language Acquisition From Object and Action Imagery0
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition0
Unified Contrastive Fusion Transformer for Multimodal Human Action Recognition0
EgoPCA: A New Framework for Egocentric Hand-Object Interaction Understanding0
IndGIC: Supervised Action Recognition under Low Illumination0
Balanced Representation Learning for Long-tailed Skeleton-based Action RecognitionCode0
Sparse Models for Machine Learning0
Improving Video Violence Recognition with Human Interaction Learning on 3D Skeleton Point Clouds0
EventTransAct: A video transformer-based framework for Event-camera based action recognition0
DD-GCN: Directed Diffusion Graph Convolutional Network for Skeleton-based Human Action RecognitionCode0
MOFO: MOtion FOcused Self-Supervision for Video UnderstandingCode0
Video BagNet: short temporal receptive fields increase robustness in long-term action recognitionCode0
Opening the Vocabulary of Egocentric ActionsCode0
Are current long-term video understanding datasets long-term?Code0
Local Spherical Harmonics Improve Skeleton-Based Hand Action RecognitionCode0
Joint learning of images and videos with a single Vision Transformer0
Temporal-Distributed Backdoor Attack Against Video Based Action Recognition0
TTPOINT: A Tensorized Point Cloud Network for Lightweight Action Recognition with Event Cameras0
Spatial-Temporal Alignment Network for Action Recognition0
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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