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 1351–1400 of 2759 papers

TitleStatusHype
CCS: Continuous Learning for Customized Incremental Wireless Sensing Services—0
Unifying Graph Embedding Features with Graph Convolutional Networks for Skeleton-based Action Recognition—0
Challenge report:VIPriors Action Recognition Challenge—0
Challenges of the Creation of a Dataset for Vision Based Human Hand Action Recognition in Industrial Assembly—0
CHAM: action recognition using convolutional hierarchical attention model—0
Channel-Temporal Attention for First-Person Video Domain Adaptation—0
ChildPlay-Hand: A Dataset of Hand Manipulations in the Wild—0
Chop & Learn: Recognizing and Generating Object-State Compositions—0
Classifying action correctness in physical rehabilitation exercises—0
Classifying Object Manipulation Actions based on Grasp-types and Motion-Constraints—0
Classifying Soccer Ball-on-Goal Position Through Kicker Shooting Action—0
Class-Incremental Learning for Action Recognition in Videos—0
CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition—0
Clean Text and Full-Body Transformer: Microsoft's Submission to the WMT22 Shared Task on Sign Language Translation—0
CLTA: Contents and Length-based Temporal Attention for Few-shot Action Recognition—0
CM2-Net: Continual Cross-Modal Mapping Network for Driver Action Recognition—0
CMAE-V: Contrastive Masked Autoencoders for Video Action Recognition—0
CNN-Based Action Recognition and Pose Estimation for Classifying Animal Behavior from Videos: A Survey—0
CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps—0
Coding Kendall's Shape Trajectories for 3D Action Recognition—0
Coherent Temporal Synthesis for Incremental Action Segmentation—0
Collaborative Attention Mechanism for Multi-View Action Recognition—0
Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition—0
Collaborative Learning for 3D Hand-Object Reconstruction and Compositional Action Recognition from Egocentric RGB Videos Using Superquadrics—0
Collaboratively Self-supervised Video Representation Learning for Action Recognition—0
Collecting and Annotating the Large Continuous Action Dataset—0
Colo-SCRL: Self-Supervised Contrastive Representation Learning for Colonoscopic Video Retrieval—0
Combating Missing Modalities in Egocentric Videos at Test Time—0
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition—0
Combining ConvNets with Hand-Crafted Features for Action Recognition Based on an HMM-SVM Classifier—0
Combining Deep Learning Classifiers for 3D Action Recognition—0
Combining Spatio-Temporal Appearance Descriptors and Optical Flow for Human Action Recognition in Video Data—0
CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices—0
Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions—0
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark—0
Complex Human Action Recognition in Live Videos Using Hybrid FR-DL Method—0
Complex Video Action Reasoning via Learnable Markov Logic Network—0
Composable Augmentation Encoding for Video Representation Learning—0
Compound Prototype Matching for Few-shot Action Recognition—0
Comprehensive Video Understanding: Video summarization with content-based video recommender design—0
Compressed Video Action Recognition with Refined Motion Vector—0
Computer Vision for Primate Behavior Analysis in the Wild—0
Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition—0
CoNFies: Controllable Neural Face Avatars—0
Context-Aware Cross-Attention for Skeleton-Based Human Action Recognition—0
Context Aware Graph Convolution for Skeleton-Based Action Recognition—0
Context-based Object Viewpoint Estimation: A 2D Relational Approach—0
Context-LSTM: a robust classifier for video detection on UCF101—0
Contextual Action Cues from Camera Sensor for Multi-Stream Action Recognition—0
Continual Learning Improves 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
4InternVideoTop-1 Accuracy77.2—Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6—Unverified
4VideoMAE V2-g3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
10Text4Vis3-fold Accuracy98.2—Unverified