SOTAVerified

Temporal Action Localization

Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.

Papers

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Showing 751–800 of 1477 papers

TitleStatusHype
Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks—0
Skeletal quads: Human action recognition using joint quadruples—0
Skeleton-based Action Recognition of People Handling Objects—0
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates—0
Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep cnn—0
Skeleton Based Action Recognition using a Stacked Denoising Autoencoder with Constraints of Privileged Information—0
Skeleton-based Action Recognition Using LSTM and CNN—0
Skeleton-Based Action Recognition with Synchronous Local and Non-local Spatio-temporal Learning and Frequency Attention—0
Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning—0
Skeleton based Activity Recognition by Fusing Part-wise Spatio-temporal and Attention Driven Residues—0
Skeleton-based Human Action Recognition via Convolutional Neural Networks (CNN)—0
Skeleton-Based Human Action Recognition with Global Context-Aware Attention LSTM Networks—0
Skeleton-Based Mutually Assisted Interacted Object Localization and Human Action Recognition—0
Relational Network for Skeleton-Based Action Recognition—0
Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space—0
Skeleton Boxes: Solving skeleton based action detection with a single deep convolutional neural network—0
Skeleton Cloud Colorization for Unsupervised 3D Action Representation Learning—0
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models—0
SkelMamba: A State Space Model for Efficient Skeleton Action Recognition of Neurological Disorders—0
Skepxels: Spatio-temporal Image Representation of Human Skeleton Joints for Action Recognition—0
Skimming and Scanning for Untrimmed Video Action Recognition—0
Sliding Dictionary Based Sparse Representation For Action Recognition—0
Slow and steady feature analysis: higher order temporal coherence in video—0
Slow Feature Analysis for Human Action Recognition—0
Slow Motion Matters: A Slow Motion Enhanced Network for Weakly Supervised Temporal Action Localization—0
SMART-Vision: Survey of Modern Action Recognition Techniques in Vision—0
SNN-Driven Multimodal Human Action Recognition via Event Camera and Skeleton Data Fusion—0
Space-Time Tree Ensemble for Action Recognition—0
Sparse and Low-Rank High-Order Tensor Regression via Parallel Proximal Method—0
Sparse Coding on Symmetric Positive Definite Manifolds using Bregman Divergences—0
Sparse Dictionary-based Attributes for Action Recognition and Summarization—0
Spatial-Temporal Pyramid Graph Reasoning for Action Recognition—0
Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition—0
Spatio-Temporal Action Localization in a Weakly Supervised Setting—0
Spatio-temporal Action Recognition: A Survey—0
Spatiotemporal Attention-based Semantic Compression for Real-time Video Recognition—0
Frequency Selective Augmentation for Video Representation Learning—0
Spatio-temporal Aware Non-negative Component Representation for Action Recognition—0
Spatio-temporal Contrastive Domain Adaptation for Action Recognition—0
Spatio-Temporal FAST 3D Convolutions for Human Action Recognition—0
Spatiotemporal Filtering for Event-Based Action Recognition—0
Spatiotemporal Fusion in 3D CNNs: A Probabilistic View—0
Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition—0
Spatiotemporal graph routing for skeleton-based action recognition—0
Spatio-temporal Human Action Localisation and Instance Segmentation in Temporally Untrimmed Videos—0
Spatio-Temporal Human Action Recognition Modelwith Flexible-interval Sampling and Normalization—0
Spatio-Temporal Instance Learning: Action Tubes from Class Supervision—0
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition—0
Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding—0
Spatiotemporal Modeling Encounters 3D Medical Image Analysis: Slice-Shift UNet with Multi-View Fusion—0
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All datasetsTHUMOS14ActivityNet-1.3HACSFineActionMultiTHUMOSCrossTaskEPIC-KITCHENS-100MUSESActivityNet-1.2Ego4D MQ testEgo4D MQ valMEXaction2

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AdaTAD (VideoMAEv2-giant)Avg mAP (0.3:0.7)76.9—Unverified
2RDFA-S6 (InternVideo2-6B)Avg mAP (0.3:0.7)74.2—Unverified
3ActionMamba(InternVideo2-6B)Avg mAP (0.3:0.7)72.72—Unverified
4GCMmAP IOU@0.172.5—Unverified
5AGT (Ours)mAP IOU@0.172.1—Unverified
6InternVideo2-6BAvg mAP (0.3:0.7)72—Unverified
7ActionFormer (InternVideo features)Avg mAP (0.3:0.7)71.58—Unverified
8TriDet (VideoMAE v2-g feature)Avg mAP (0.3:0.7)70.1—Unverified
9InternVideo2-1BAvg mAP (0.3:0.7)69.8—Unverified
10ActionFormer (VideoMAE V2-g features)Avg mAP (0.3:0.7)69.6—Unverified
#ModelMetricClaimedVerifiedStatus
1UnLoc-LmAP IOU@0.559.3—Unverified
2RDFA-S6 (InternVideo2-6B)mAP42.9—Unverified
3ActionMamba (InternVideo2-6B)mAP42.02—Unverified
4PRN+BMN (ensemble)mAP42—Unverified
5AdaTAD (VideoMAEv2-giant)mAP41.93—Unverified
6InternVideo2-6BmAP41.2—Unverified
7InternVideo2-1BmAP40.4—Unverified
8UniMD+Sync.mAP39.83—Unverified
9PRN (CSN)mAP39.4—Unverified
10InternVideomAP39—Unverified
#ModelMetricClaimedVerifiedStatus
1RDFA-S6 (InternVideo2-6B)Average-mAP45.8—Unverified
2ActionMamba(InternVideo2-6B)Average-mAP44.56—Unverified
3DyFADet(VideoMAEv2)Average-mAP44.3—Unverified
4InternVideo2-6BAverage-mAP43.3—Unverified
5TriDet (VideoMAEv2)Average-mAP43.1—Unverified
6InternVideo2-1BAverage-mAP42.4—Unverified
7InternVideoAverage-mAP41.55—Unverified
8TriDet (SlowFast)Average-mAP38.6—Unverified
9TriDet (I3D RGB)Average-mAP36.8—Unverified
10TadTr (I3D RGB)Average-mAP32.09—Unverified
#ModelMetricClaimedVerifiedStatus
1RDFA-S6 (InternVideo2-6B)mAP29.6—Unverified
2ActionMamba(InternVideo2-6B)mAP29.04—Unverified
3InternVideo2-6BmAP27.7—Unverified
4DyFADet (VideoMAE v2-g)mAP23.8—Unverified
5VideoMAE V2-gmAP18.24—Unverified
6InternVideomAP17.57—Unverified
7BMN (i3d feaure)mAP9.25—Unverified
8G-TAD (i3d feature)mAP9.06—Unverified
9DBG (i3d feature)mAP6.75—Unverified
#ModelMetricClaimedVerifiedStatus
1TriDet (VideoMAEv2)Average mAP37.5—Unverified
2DualDETR (I3D-rgb)Average mAP32.64—Unverified
3TriDet (I3D-rgb)Average mAP30.7—Unverified
4TemporalMaxerAverage mAP29.9—Unverified
5PointTADAverage mAP23.5—Unverified
6PDANAverage mAP17.3—Unverified
7MS-TCTAverage mAP16.2—Unverified
8MLADAverage mAP14.2—Unverified
#ModelMetricClaimedVerifiedStatus
1VideoCLIPRecall47.3—Unverified
2VLMRecall46.5—Unverified
3TACoRecall42.5—Unverified
4Text-Video EmbeddingRecall33.6—Unverified
5Fully-supervised upper-boundRecall31.6—Unverified
6ZhukovRecall22.4—Unverified
7AlayracRecall13.3—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaTAD (verb, VideoMAE-L)Avg mAP (0.1-0.5)29.3—Unverified
2TriDet (verb)Avg mAP (0.1-0.5)25.4—Unverified
3TemporalMaxer (verb)Avg mAP (0.1-0.5)24.5—Unverified
4ActionFormer (verb)Avg mAP (0.1-0.5)23.5—Unverified
5G-TAD (verb)Avg mAP (0.1-0.5)9.4—Unverified
6BMN (verb)Avg mAP (0.1-0.5)8.4—Unverified
#ModelMetricClaimedVerifiedStatus
1TemporalMaxermAP27.2—Unverified
2MUSESmAP18.6—Unverified
#ModelMetricClaimedVerifiedStatus
1DeepMetricLearnermAP IOU@0.535.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ActionFormer (SlowFast+Omnivore+EgoVLP)Average mAP21.76—Unverified
#ModelMetricClaimedVerifiedStatus
1ActionFormer (SlowFast+Omnivore+EgoVLP)Average mAP21.4—Unverified
#ModelMetricClaimedVerifiedStatus
1S-CNNmAP7.4—Unverified