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 151200 of 2759 papers

TitleStatusHype
Dual Contrastive Prediction for Incomplete Multi-view Representation LearningCode1
Dynamic Perceiver for Efficient Visual RecognitionCode1
Actor-Context-Actor Relation Network for Spatio-Temporal Action LocalizationCode1
DSANet: Dynamic Segment Aggregation Network for Video-Level Representation LearningCode1
Do Language Models Understand Time?Code1
Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video ClassificationCode1
Dual-path Adaptation from Image to Video TransformersCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
DSTSA-GCN: Advancing Skeleton-Based Gesture Recognition with Semantic-Aware Spatio-Temporal Topology ModelingCode1
E^2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action RecognitionCode1
Audio-Visual Instance Discrimination with Cross-Modal AgreementCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
AR-Net: Adaptive Frame Resolution for Efficient Action RecognitionCode1
3DV: 3D Dynamic Voxel for Action Recognition in Depth VideoCode1
Action Genome: Actions as Composition of Spatio-temporal Scene GraphsCode1
Augmented Neural Fine-Tuning for Efficient Backdoor PurificationCode1
ActionCLIP: A New Paradigm for Video Action RecognitionCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
AutoVideo: An Automated Video Action Recognition SystemCode1
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual ActionsCode1
AViD Dataset: Anonymized Videos from Diverse CountriesCode1
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic InformationCode1
Disentangled Non-Local Neural NetworksCode1
A Dense-Sparse Complementary Network for Human Action Recognition based on RGB and Skeleton ModalitiesCode1
ArtEmis: Affective Language for Visual ArtCode1
Benchmarking Micro-action Recognition: Dataset, Methods, and ApplicationsCode1
Elaborative Rehearsal for Zero-shot Action RecognitionCode1
BASAR:Black-box Attack on Skeletal Action RecognitionCode1
ARID: A New Dataset for Recognizing Action in the DarkCode1
End-to-End Streaming Video Temporal Action Segmentation with Reinforce LearningCode1
Discover and Mitigate Unknown Biases with Debiasing Alternate NetworksCode1
BEVT: BERT Pretraining of Video TransformersCode1
Disentangled Pre-training for Human-Object Interaction DetectionCode1
Bringing Online Egocentric Action Recognition into the wildCode1
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion PerceptionCode1
Approximated Bilinear Modules for Temporal ModelingCode1
ACTION-Net: Multipath Excitation for Action RecognitionCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
Eventful Transformers: Leveraging Temporal Redundancy in Vision TransformersCode1
EventRPG: Event Data Augmentation with Relevance Propagation GuidanceCode1
3D CNNs with Adaptive Temporal Feature ResolutionsCode1
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action RecognitionCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D NetworksCode1
CAST: Cross-Attention in Space and Time for Video Action RecognitionCode1
Challenges in Video-Based Infant Action Recognition: A Critical Examination of the State of the ArtCode1
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
Full-Body Articulated Human-Object InteractionCode1
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action RecognitionCode1
DEVIAS: Learning Disentangled Video Representations of Action and SceneCode1
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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