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 11761200 of 2759 papers

TitleStatusHype
3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning0
Federated Action Recognition on Heterogeneous Embedded Devices0
Feature-Supervised Action Modality Transfer0
Feature Sampling Strategies for Action Recognition0
Channel-Temporal Attention for First-Person Video Domain Adaptation0
Feature sampling and partitioning for visual vocabulary generation on large action classification datasets0
Featureless: Bypassing feature extraction in action categorization0
CHAM: action recognition using convolutional hierarchical attention model0
Feature Hallucination for Self-supervised Action Recognition0
Challenges of the Creation of a Dataset for Vision Based Human Hand Action Recognition in Industrial Assembly0
An Action Recognition network for specific target based on rMC and RPN0
Action Recognition in the Frequency Domain0
Feature and Region Selection for Visual Learning0
FBK-HUPBA Submission to the EPIC-Kitchens Action Recognition 2020 Challenge0
FBK-HUPBA Submission to the EPIC-Kitchens 2019 Action Recognition Challenge0
Challenge report:VIPriors Action Recognition Challenge0
Fast Temporal Activity Proposals for Efficient Detection of Human Actions in Untrimmed Videos0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning0
Fast, invariant representation for human action in the visual system0
Action recognition in still images by latent superpixel classification0
A compact sequence encoding scheme for online human activity recognition in HRI applications0
FASTER Recurrent Networks for Efficient Video Classification0
Faster and Accurate Compressed Video Action Recognition Straight from the Frequency Domain0
Unifying Graph Embedding Features with Graph Convolutional Networks for Skeleton-based Action Recognition0
FACTS: Fine-Grained Action Classification for Tactical Sports0
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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