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

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Showing 1101–1150 of 2759 papers

TitleStatusHype
Collaboratively Self-supervised Video Representation Learning for Action Recognition—0
Frequency-aware Event Cloud Network—0
Collaborative Learning for 3D Hand-Object Reconstruction and Compositional Action Recognition from Egocentric RGB Videos Using Superquadrics—0
End-to-End Video Captioning—0
Free-Form Composition Networks for Egocentric Action Recognition—0
Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition—0
Frame Order Matters: A Temporal Sequence-Aware Model for Few-Shot Action Recognition—0
Collaborative Attention Mechanism for Multi-View Action Recognition—0
An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs—0
fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs—0
Fourier-based Action Recognition for Wildlife Behavior Quantification with Event Cameras—0
Coherent Temporal Synthesis for Incremental Action Segmentation—0
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal—0
Action Recognition using Transfer Learning and Majority Voting for CSGO—0
ForcePose: A Deep Learning Approach for Force Calculation Based on Action Recognition Using MediaPipe Pose Estimation Combined with Object Detection—0
Force From Motion: Decoding Physical Sensation in a First Person Video—0
Focusing and Diffusion: Bidirectional Attentive Graph Convolutional Networks for Skeleton-based Action Recognition—0
Focalized Contrastive View-invariant Learning for Self-supervised Skeleton-based Action Recognition—0
Coding Kendall's Shape Trajectories for 3D Action Recognition—0
An Effective End-to-End Solution for Multimodal Action Recognition—0
Focal and Global Spatial-Temporal Transformer for Skeleton-based Action Recognition—0
FMM-X3D: FPGA-based modeling and mapping of X3D for Human Action Recognition—0
Flow Dynamics Correction for Action Recognition—0
Anchor-Based Spatio-Temporal Attention 3D Convolutional Networks for Dynamic 3D Point Cloud Sequences—0
Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition—0
FlowCaps: Optical Flow Estimation with Capsule Networks For Action Recognition—0
Flip-Invariant Motion Representation—0
CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps—0
An Attention-Enhanced Recurrent Graph Convolutional Network for Skeleton-Based Action Recognition—0
Flatten: Video Action Recognition is an Image Classification task—0
Fitting, Comparison, and Alignment of Trajectories on Positive Semi-Definite Matrices with Application to Action Recognition—0
CNN-Based Action Recognition and Pose Estimation for Classifying Animal Behavior from Videos: A Survey—0
An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition—0
Action Recognition Using Supervised Spiking Neural Networks—0
A Comprehensive Survey on Architectural Advances in Deep CNNs: Challenges, Applications, and Emerging Research Directions—0
3D Human motion anticipation and classification—0
CMAE-V: Contrastive Masked Autoencoders for Video Action Recognition—0
First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos—0
CM2-Net: Continual Cross-Modal Mapping Network for Driver Action Recognition—0
An Approach to Pose-Based Action Recognition—0
First Person Action Recognition Using Deep Learned Descriptors—0
FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition—0
CLTA: Contents and Length-based Temporal Attention for Few-shot Action Recognition—0
Action Recognition in Video Using Sparse Coding and Relative Features—0
FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding—0
Fine-grained Video Categorization with Redundancy Reduction Attention—0
Clean Text and Full-Body Transformer: Microsoft's Submission to the WMT22 Shared Task on Sign Language Translation—0
Fine-Grained Side Information Guided Dual-Prompts for Zero-Shot Skeleton Action Recognition—0
Fine-grained Multi-Modal Self-Supervised Learning—0
CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition—0
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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