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 17011725 of 2759 papers

TitleStatusHype
FBK-HUPBA Submission to the EPIC-Kitchens Action Recognition 2020 Challenge0
Rescaling Egocentric VisionCode1
Motion Representation Using Residual Frames with 3D CNNCode1
Sequential Feature Filtering Classifier0
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual RecognitionCode1
Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation LearningCode1
A Real-time Action Representation with Temporal Encoding and Deep Compression0
Learn to cycle: Time-consistent feature discovery for action recognitionCode0
Actor-Context-Actor Relation Network for Spatio-Temporal Action LocalizationCode1
3DFCNN: Real-Time Action Recognition using 3D Deep Neural Networks with Raw Depth Information0
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks0
DTG-Net: Differentiated Teachers Guided Self-Supervised Video Action Recognition0
Iterate & Cluster: Iterative Semi-Supervised Action RecognitionCode1
Disentangled Non-Local Neural NetworksCode1
Interferometric Graph Transform: a Deep Unsupervised Graph RepresentationCode1
PNL: Efficient Long-Range Dependencies Extraction with Pyramid Non-Local Module for Action Recognition0
Action Recognition with Deep Multiple Aggregation Networks0
Deep hierarchical pooling design for cross-granularity action recognition0
ARID: A New Dataset for Recognizing Action in the DarkCode1
WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos0
Action Genome: Actions As Compositions of Spatio-Temporal Scene Graphs0
Skeleton-Based Action Recognition With Shift Graph Convolutional NetworkCode1
Attention-Based Context Aware Reasoning for Situation RecognitionCode1
Regularization on Spatio-Temporally Smoothed Feature for Action Recognition0
Context Aware Graph Convolution for Skeleton-Based Action Recognition0
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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