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 26262650 of 2759 papers

TitleStatusHype
Long-Range Trajectories from Global and Local Motion Representations0
Hyper-Fisher Vectors for Action Recognition0
Bio-Inspired Human Action Recognition using Hybrid Max-Product Neuro-Fuzzy Classifier and Quantum-Behaved PSO0
Manipulated Object Proposal: A Discriminative Object Extraction and Feature Fusion Framework for First-Person Daily Activity Recognition0
Action Recognition by Hierarchical Mid-level Action Elements0
Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos0
Action Recognition based on Subdivision-Fusion Model0
Multimodal Multipart Learning for Action Recognition in Depth Videos0
Action recognition in still images by latent superpixel classification0
Every Moment Counts: Dense Detailed Labeling of Actions in Complex VideosCode0
Towards Good Practices for Very Deep Two-Stream ConvNetsCode1
Time Series Classification using the Hidden-Unit Logistic Model0
Slow and steady feature analysis: higher order temporal coherence in video0
P-CNN: Pose-based CNN Features for Action Recognition0
Hierarchical recurrent neural network for skeleton based action recognition0
First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos0
Modeling Video Evolution for Action Recognition0
Space-Time Tree Ensemble for Action Recognition0
Interaction Part Mining: A Mid-Level Approach for Fine-Grained Action Recognition0
Learning a Non-Linear Knowledge Transfer Model for Cross-View Action Recognition0
Can Humans Fly? Action Understanding With Multiple Classes of Actors0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting0
Multi-Feature Max-Margin Hierarchical Bayesian Model for Action Recognition0
Bilinear Heterogeneous Information Machine for RGB-D Action Recognition0
ActivityNet: A Large-Scale Video Benchmark for Human Activity UnderstandingCode0
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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