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 21512175 of 2759 papers

TitleStatusHype
Compressing Recurrent Neural Networks with Tensor Ring for Action RecognitionCode1
Higher-order Network for Action Recognition0
Relational Long Short-Term Memory for Video Action Recognition0
A Perceptual Prediction Framework for Self Supervised Event SegmentationCode0
Skeleton-Based Action Recognition with Synchronous Local and Non-local Spatio-temporal Learning and Frequency Attention0
Cross and Learn: Cross-Modal Self-SupervisionCode0
Leveraging Random Label Memorization for Unsupervised Pre-Training0
StNet: Local and Global Spatial-Temporal Modeling for Action RecognitionCode0
Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition0
Random Temporal Skipping for Multirate Video Analysis0
DeepGRU: Deep Gesture Recognition UtilityCode0
Informed Democracy: Voting-based Novelty Detection for Action Recognition0
ActionXPose: A Novel 2D Multi-view Pose-based Algorithm for Real-time Human Action Recognition0
A^2-Nets: Double Attention Networks0
Real-time Action Recognition with Dissimilarity-based Training of Specialized Module Networks0
Fine-grained Video Categorization with Redundancy Reduction Attention0
Learning with privileged information via adversarial discriminative modality distillationCode0
Cross-Modal and Hierarchical Modeling of Video and TextCode0
Incremental Deep Learning for Robust Object Detection in Unknown Cluttered Environments0
Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANsCode1
Representation Flow for Action RecognitionCode0
Interpretable Spatio-temporal Attention for Video Action Recognition0
Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural NetworksCode0
Part-based Graph Convolutional Network for Action RecognitionCode0
Temporal-Spatial Mapping for 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