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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2301–2350 of 2759 papers

TitleStatusHype
Deja Vu: Motion Prediction in Static ImagesCode0
Featureless: Bypassing feature extraction in action categorization—0
Depth Pooling Based Large-scale 3D Action Recognition with Convolutional Neural Networks—0
Analysis of Hand Segmentation in the WildCode0
Learning clip representations for skeleton-based 3d action recognition—0
Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition—0
2D/3D Pose Estimation and Action Recognition using Multitask Deep LearningCode0
Real-Time End-to-End Action Detection with Two-Stream Networks—0
Glimpse Clouds: Human Activity Recognition from Unstructured Feature PointsCode0
Learning Representative Temporal Features for Action Recognition—0
Fisherposes for Human Action Recognition Using Kinect Sensor DataCode0
Musical Chair: Efficient Real-Time Recognition Using Collaborative IoT Devices—0
Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model—0
Deep-Temporal LSTM for Daily Living Action Recognition—0
Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences—0
Histogram of Oriented Depth Gradients for Action Recognition—0
A Generative Approach to Zero-Shot and Few-Shot Action Recognition—0
Let's Dance: Learning From Online Dance VideosCode0
DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial Networks—0
Semi-supervised Fisher vector network—0
Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition—0
Moments in Time Dataset: one million videos for event understandingCode0
Ensemble One-dimensional Convolution Neural Networks for Skeleton-based Action Recognition—0
What have we learned from deep representations for action recognition?—0
Distributed non-parametric deep and wide networks—0
A Unified Method for First and Third Person Action Recognition—0
HACS: Human Action Clips and Segments Dataset for Recognition and Temporal LocalizationCode0
On the Integration of Optical Flow and Action Recognition—0
Human Action Recognition: Pose-based Attention draws focus to Hands—0
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition—0
Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video ClassificationCode0
Deception Detection in Videos—0
Im2Flow: Motion Hallucination from Static Images for Action RecognitionCode0
Cooperative Training of Deep Aggregation Networks for RGB-D Action Recognition—0
Robust 3D Action Recognition through Sampling Local Appearances and Global Distributions—0
Multimodal Visual Concept Learning with Weakly Supervised TechniquesCode0
Compressed Video Action RecognitionCode0
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks—0
Label Efficient Learning of Transferable Representations across Domains and Tasks—0
Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action RecognitionCode0
Scalable and Compact 3D Action Recognition with Approximated RBF Kernel Machines—0
Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN FeaturesCode0
Revisiting hand-crafted feature for action recognition: a set of improved dense trajectoriesCode0
Highly Efficient Human Action Recognition with Quantum Genetic Algorithm Optimized Support Vector Machine—0
Predictive Learning: Using Future Representation Learning Variantial Autoencoder for Human Action Prediction—0
Appearance-and-Relation Networks for Video ClassificationCode0
Temporal Relational Reasoning in VideosCode0
Train, Diagnose and Fix: Interpretable Approach for Fine-grained Action Recognition—0
Multi-Level Recurrent Residual Networks for Action Recognition—0
Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion—0
Show:102550
← PrevPage 47 of 56Next →
All datasetsSomething-Something V2UCF101HMDB-51Something-Something V1AVA v2.2EPIC-KITCHENS-100NTU RGB+DNTU RGB+D 120Diving-48ActivityNetAVA v2.1H2O (2 Hands and Objects)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4—Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1—Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3—Unverified
4DejaVidTop-1 Accuracy77.2—Unverified
5InternVideoTop-1 Accuracy77.2—Unverified
6InternVideo2-1BTop-1 Accuracy77.1—Unverified
7VideoMAE V2-gTop-1 Accuracy77—Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7—Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5—Unverified
10TubeViT-LTop-1 Accuracy76.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7—Unverified
2OmniVec23-fold Accuracy99.6—Unverified
3VideoMAE V2-g3-fold Accuracy99.6—Unverified
4OmniVec3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
10LGD-3D Two-stream3-fold Accuracy98.2—Unverified