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 9511000 of 2759 papers

TitleStatusHype
Consistency Prototype Module and Motion Compensation for Few-Shot Action Recognition (CLIP-CPM^2C)Code0
Action Recognition in Video Recordings from Gynecologic Laparoscopy0
LEAP: LLM-Generation of Egocentric Action Programs0
GeoDeformer: Geometric Deformable Transformer for Action Recognition0
Generative Hierarchical Temporal Transformer for Hand Pose and Action Modeling0
PALM: Predicting Actions through Language Models0
Object-based (yet Class-agnostic) Video Domain Adaptation0
F4D: Factorized 4D Convolutional Neural Network for Efficient Video-level Representation Learning0
Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition0
Align before Adapt: Leveraging Entity-to-Region Alignments for Generalizable Video Action Recognition0
REACT: Recognize Every Action Everywhere All At Once0
Multi-modal Instance Refinement for Cross-domain Action Recognition0
UniHPE: Towards Unified Human Pose Estimation via Contrastive Learning0
Modality Mixer Exploiting Complementary Information for Multi-modal Action Recognition0
GLAD: Global-Local View Alignment and Background Debiasing for Unsupervised Video Domain Adaptation with Large Domain GapCode0
VLM-Eval: A General Evaluation on Video Large Language Models0
MVSA-Net: Multi-View State-Action Recognition for Robust and Deployable Trajectory Generation0
SkelVIT: Consensus of Vision Transformers for a Lightweight Skeleton-Based Action Recognition System0
Semantic-aware Video Representation for Few-shot Action Recognition0
Learning Human Action Recognition Representations Without Real HumansCode0
Asymmetric Masked Distillation for Pre-Training Small Foundation ModelsCode0
FPGA-QHAR: Throughput-Optimized for Quantized Human Action Recognition on The EdgeCode0
Distilling Knowledge from CNN-Transformer Models for Enhanced Human Action Recognition0
ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab0
Distribution of Action Movements (DAM): A Descriptor for Human Action Recognition0
Videoprompter: an ensemble of foundational models for zero-shot video understanding0
S3Aug: Segmentation, Sampling, and Shift for Action Recognition0
Human Pose-based Estimation, Tracking and Action Recognition with Deep Learning: A Survey0
Deep Learning Techniques for Video Instance Segmentation: A Survey0
Flow Dynamics Correction for Action Recognition0
Few-shot Action Recognition with Captioning Foundation Models0
Proving the Potential of Skeleton Based Action Recognition to Automate the Analysis of Manual Processes0
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition0
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks0
Graph learning in robotics: a survey0
PoseAction: Action Recognition for Patients in the Ward using Deep Learning Approaches0
Beyond the Benchmark: Detecting Diverse Anomalies in VideosCode0
Action Recognition Utilizing YGAR Dataset0
A Hierarchical Graph-based Approach for Recognition and Description Generation of Bimanual Actions in Videos0
Telling Stories for Common Sense Zero-Shot Action RecognitionCode0
Position and Orientation-Aware One-Shot Learning for Medical Action Recognition from Signal Data0
M^33D: Learning 3D priors using Multi-Modal Masked Autoencoders for 2D image and video understanding0
Chop & Learn: Recognizing and Generating Object-State Compositions0
Boundary-Aware Proposal Generation Method for Temporal Action Localization0
Egocentric RGB+Depth Action Recognition in Industry-Like SettingsCode0
S3TC: Spiking Separated Spatial and Temporal Convolutions with Unsupervised STDP-based Learning for Action Recognition0
Elevating Skeleton-Based Action Recognition with Efficient Multi-Modality Self-SupervisionCode0
Survey of Action Recognition, Spotting and Spatio-Temporal Localization in Soccer -- Current Trends and Research Perspectives0
CPR-Coach: Recognizing Composite Error Actions based on Single-class Training0
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild0
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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