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 23012325 of 2759 papers

TitleStatusHype
Adaptive and Iteratively Improving Recurrent Lateral ConnectionsCode0
Gate-Shift-Fuse for Video Action RecognitionCode0
Uncertainty-DTW for Time Series and SequencesCode0
Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web ImagesCode0
Sequence-to-Sequence Modeling for Action Identification at High Temporal ResolutionCode0
Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image DatasetsCode0
Action Recognition for Privacy-Preserving Ambient Assisted LivingCode0
Multi-level Second-order Few-shot LearningCode0
CoTeRe-Net: Discovering Collaborative Ternary Relations in VideosCode0
FT-HID: A Large Scale RGB-D Dataset for First and Third Person Human Interaction AnalysisCode0
Multimodal Attack Detection for Action Recognition ModelsCode0
Convolutional Two-Stream Network Fusion for Video Action RecognitionCode0
Moments in Time Dataset: one million videos for event understandingCode0
MOFO: MOtion FOcused Self-Supervision for Video UnderstandingCode0
FSBench: A Figure Skating Benchmark for Advancing Artistic Sports UnderstandingCode0
MaCLR: Motion-aware Contrastive Learning of Representations for VideosCode0
From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive HydronephrosisCode0
From Forest to Zoo: Great Ape Behavior Recognition with ChimpBehaveCode0
Modeling the Relative Visual Tempo for Self-supervised Skeleton-based Action RecognitionCode0
ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome PredictionCode0
Shifting Perspective to See Difference: A Novel Multi-View Method for Skeleton based Action RecognitionCode0
Modality Distillation with Multiple Stream Networks for Action RecognitionCode0
Multimodal Task-Driven Dictionary Learning for Image ClassificationCode0
X4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos through Cross-modal Knowledge TransferCode0
Action Recognition for Depth Video using Multi-view Dynamic ImagesCode0
Show:102550
← PrevPage 93 of 111Next →

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