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 301325 of 2759 papers

TitleStatusHype
Dynamic Perceiver for Efficient Visual RecognitionCode1
E^2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action RecognitionCode1
CoCon: Cooperative-Contrastive LearningCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity UnderstandingCode1
EgoNCE++: Do Egocentric Video-Language Models Really Understand Hand-Object Interactions?Code1
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the BackboneCode1
Elaborative Rehearsal for Zero-shot Action RecognitionCode1
Actor-Context-Actor Relation Network for Spatio-Temporal Action LocalizationCode1
End-to-End Learning of Visual Representations from Uncurated Instructional VideosCode1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action RecognitionCode1
EPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language modelsCode1
Epic-Sounds: A Large-scale Dataset of Actions That SoundCode1
Eventful Transformers: Leveraging Temporal Redundancy in Vision TransformersCode1
EventRPG: Event Data Augmentation with Relevance Propagation GuidanceCode1
CIDEr: Consensus-based Image Description EvaluationCode1
ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and MoreCode1
A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion RecognitionCode1
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action RecognitionCode1
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction AlignmentCode1
Federated Self-supervised Learning for Video UnderstandingCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
Fisher Information guided Purification against Backdoor AttacksCode1
Full-Body Articulated Human-Object InteractionCode1
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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