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 18511875 of 2759 papers

TitleStatusHype
Synthetic Humans for Action Recognition from Unseen ViewpointsCode0
VideoDG: Generalizing Temporal Relations in Videos to Novel DomainsCode0
View-invariant Deep Architecture for Human Action Recognition using late fusion0
Spatio-Temporal Pyramid Graph Convolutions for Human Action Recognition and Postural Assessment0
RSA: Randomized Simulation as Augmentation for Robust Human Action Recognition0
View-Invariant Probabilistic Embedding for Human PoseCode0
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal AggregationCode0
A Multigrid Method for Efficiently Training Video ModelsCode1
Skeleton based Activity Recognition by Fusing Part-wise Spatio-temporal and Attention Driven Residues0
Exploiting Motion Information from Unlabeled Videos for Static Image Action Recognition0
Gate-Shift Networks for Video Action RecognitionCode0
Sparse and Low-Rank High-Order Tensor Regression via Parallel Proximal Method0
Self-Supervised Learning by Cross-Modal Audio-Video ClusteringCode0
Action Recognition via Pose-Based Graph Convolutional Networks with Intermediate Dense Supervision0
An Attention-Enhanced Recurrent Graph Convolutional Network for Skeleton-Based Action Recognition0
PREDICT & CLUSTER: Unsupervised Skeleton Based Action RecognitionCode1
Literature Review of Action Recognition in the Wild0
AdapNet: Adaptability Decomposing Encoder-Decoder Network for Weakly Supervised Action Recognition and Localization0
Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space0
Deep Image-to-Video Adaptation and Fusion Networks for Action Recognition0
Gating Revisited: Deep Multi-layer RNNs That Can Be TrainedCode0
TEINet: Towards an Efficient Architecture for Video Recognition0
Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping0
MMTM: Multimodal Transfer Module for CNN FusionCode0
Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain0
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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
4InternVideoTop-1 Accuracy77.2Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6Unverified
4VideoMAE V2-g3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified