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 801825 of 2759 papers

TitleStatusHype
Learning To Score Olympic EventsCode0
Learn to cycle: Time-consistent feature discovery for action recognitionCode0
Learning Spatio-Temporal Features with 3D Residual Networks for Action RecognitionCode0
Attentive Semantic Video Generation using CaptionsCode0
Learning Skeletal Graph Neural Networks for Hard 3D Pose EstimationCode0
Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction RecognitionCode0
Learning Human Action Recognition Representations Without Real HumansCode0
Learning long-term dependencies for action recognition with a biologically-inspired deep networkCode0
Delving Deeper into Convolutional Networks for Learning Video RepresentationsCode0
Learning from Video and Text via Large-Scale Discriminative ClusteringCode0
Deja Vu: Motion Prediction in Static ImagesCode0
DejaVid: Encoder-Agnostic Learned Temporal Matching for Video ClassificationCode0
Learning Gating ConvNet for Two-Stream based Methods in Action RecognitionCode0
Attention Bottlenecks for Multimodal FusionCode0
Adaptive frame selection in two dimensional convolutional neural network action recognitionCode0
Learning from Temporal Spatial Cubism for Cross-Dataset Skeleton-based Action RecognitionCode0
Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural SearchingCode0
Learning Spatio-Temporal Representation with Local and Global DiffusionCode0
Large-scale weakly-supervised pre-training for video action recognitionCode0
Adaptive and Iteratively Improving Recurrent Lateral ConnectionsCode0
Real-Time Action Detection in Video Surveillance using Sub-Action Descriptor with Multi-CNNCode0
Learning Actor Relation Graphs for Group Activity RecognitionCode0
Attentional Pooling for Action RecognitionCode0
Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie StimuliCode0
Language Model Guided Interpretable Video Action ReasoningCode0
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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