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 26512675 of 2759 papers

TitleStatusHype
Leveraging Foundation Model Automatic Data Augmentation Strategies and Skeletal Points for Hands Action Recognition in Industrial Assembly Lines0
Leveraging Foundation Models for Multimodal Graph-Based Action Recognition0
Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition0
Towards Achieving Perfect Multimodal Alignment0
Leveraging Random Label Memorization for Unsupervised Pre-Training0
Leveraging Self-Supervised Training for Unintentional Action Recognition0
Leveraging Temporal Context in Low Representational Power Regimes0
Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition0
Leveraging YOLO-World and GPT-4V LMMs for Zero-Shot Person Detection and Action Recognition in Drone Imagery0
Lie-X: Depth Image Based Articulated Object Pose Estimation, Tracking, and Action Recognition on Lie Groups0
LIGAR: Lightweight General-purpose Action Recognition0
Lighter Stacked Hourglass Human Pose Estimation0
Lightweight Delivery Detection on Doorbell Cameras0
Linear-time Online Action Detection From 3D Skeletal Data Using Bags of Gesturelets0
Literature Review of Action Recognition in the Wild0
Livestock Monitoring with Transformer0
LLMs are Good Action Recognizers0
Locality preserving projection on SPD matrix Lie group: algorithm and analysis0
Localized Trajectories for 2D and 3D Action Recognition0
LocATe: End-to-end Localization of Actions in 3D with Transformers0
Log-Euclidean Bag of Words for Human Action Recognition0
LoKi: Low-dimensional KAN for Efficient Fine-tuning Image Models0
Long-Range Trajectories from Global and Local Motion Representations0
Long-Short Temporal Contrastive Learning of Video Transformers0
Long-Short Temporal Modeling for Efficient 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