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 176200 of 2759 papers

TitleStatusHype
Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action RecognitionCode1
Deep Analysis of CNN-based Spatio-temporal Representations for Action RecognitionCode1
Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and DataCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
BMN: Boundary-Matching Network for Temporal Action Proposal GenerationCode1
Depth Guided Adaptive Meta-Fusion Network for Few-shot Video RecognitionCode1
DEVIAS: Learning Disentangled Video Representations of Action and SceneCode1
ActionCLIP: A New Paradigm for Video Action RecognitionCode1
Disentangled Pre-training for Human-Object Interaction DetectionCode1
Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video ClassificationCode1
Do Language Models Understand Time?Code1
ACTION-Net: Multipath Excitation for Action RecognitionCode1
DSANet: Dynamic Segment Aggregation Network for Video-Level Representation LearningCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
Dual-path Adaptation from Image to Video TransformersCode1
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion PerceptionCode1
An Action Is Worth Multiple Words: Handling Ambiguity in Action RecognitionCode1
Bringing Online Egocentric Action Recognition into the wildCode1
EgoAdapt: A multi-stream evaluation study of adaptation to real-world egocentric user videoCode1
Benchmarking Micro-action Recognition: Dataset, Methods, and ApplicationsCode1
EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery VideosCode1
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the BackboneCode1
Elaborative Rehearsal for Zero-shot Action RecognitionCode1
Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the MotionCode1
BASAR:Black-box Attack on Skeletal Action RecognitionCode1
Show:102550
← PrevPage 8 of 111Next →

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