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 251–300 of 1477 papers

TitleStatusHype
CAG-QIL: Context-Aware Actionness Grouping via Q Imitation Learning for Online Temporal Action Localization—0
Deep manifold-to-manifold transforming network for action recognition—0
CAMREP- Concordia Action and Motion Repository—0
Can Humans Fly? Action Understanding With Multiple Classes of Actors—0
Blockwise Temporal-Spatial Pathway Network—0
Bio-Inspired Human Action Recognition using Hybrid Max-Product Neuro-Fuzzy Classifier and Quantum-Behaved PSO—0
Advances in Human Action Recognition: A Survey—0
Binary Coding for Partial Action Analysis With Limited Observation Ratios—0
Bilinear Heterogeneous Information Machine for RGB-D Action Recognition—0
ADM-Loc: Actionness Distribution Modeling for Point-supervised Temporal Action Localization—0
Action Recognition Based on Joint Trajectory Maps with Convolutional Neural Networks—0
BID: Boundary-Interior Decoding for Unsupervised Temporal Action Localization Pre-Trainin—0
A discussion on the validation tests employed to compare human action recognition methods using the MSR Action3D dataset—0
Beyond Spatial Pyramid Matching: Space-time Extended Descriptor for Action Recognition—0
Beyond Gaussian Pyramid: Multi-skip Feature Stacking for Action Recognition—0
3D Convolutional with Attention for Action Recognition—0
Deep Learning Computer Vision Algorithms for Real-time UAVs On-board Camera Image Processing—0
Deep Motion Features for Visual Tracking—0
Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition—0
Beyond Covariance: Feature Representation With Nonlinear Kernel Matrices—0
Better Exploiting Motion for Better Action Recognition—0
A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data—0
Benchmarking Data Efficiency and Computational Efficiency of Temporal Action Localization Models—0
Benchmarking Conventional Vision Models on Neuromorphic Fall Detection and Action Recognition Dataset—0
Adding Attentiveness to the Neurons in Recurrent Neural Networks—0
Bayesian Non-Parametric Inference for Manifold Based MoCap Representation—0
AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos—0
Adaptive RNN Tree for Large-Scale Human Action Recognition—0
Bag of Visual Words and Fusion Methods for Action Recognition: Comprehensive Study and Good Practice—0
3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfaces—0
Deep Discriminative Model for Video Classification—0
Knowledge Distillation for Human Action Anticipation—0
Adaptive Perception Transformer for Temporal Action Localization—0
Adaptive Mutual Supervision for Weakly-Supervised Temporal Action Localization—0
Actionness Estimation Using Hybrid Fully Convolutional Networks—0
BabyNet: A Lightweight Network for Infant Reaching Action Recognition in Unconstrained Environments to Support Future Pediatric Rehabilitation Applications—0
Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections—0
AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoning—0
Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures—0
Actionness-Assisted Recognition of Actions—0
Accuracy and Performance Comparison of Video Action Recognition Approaches—0
DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization—0
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition—0
Action Machine: Rethinking Action Recognition in Trimmed Videos—0
A Variational Information Bottleneck Based Method to Compress Sequential Networks for Human Action Recognition—0
Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition—0
Automatic Curation of Golf Highlights using Multimodal Excitement Features—0
Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization—0
AutoLoc: Weakly-supervised Temporal Action Localization in Untrimmed Videos—0
A Cause and Effect Analysis of Motion Trajectories for Modeling Actions—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