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 1351–1400 of 1477 papers

TitleStatusHype
Forcing the Whole Video as Background: An Adversarial Learning Strategy for Weakly Temporal Action Localization—0
fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs—0
Free-Form Composition Networks for Egocentric Action Recognition—0
From CNNs to Transformers in Multimodal Human Action Recognition: A Survey—0
From Detection to Action Recognition: An Edge-Based Pipeline for Robot Human Perception—0
From Pose to Activity: Surveying Datasets and Introducing CONVERSE—0
From Synsets to Videos: Enriching ItalWordNet Multimodally—0
Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition—0
Fusing Deep Convolutional Networks for Large Scale Visual Concept Classification—0
Fusing Hand and Body Skeletons for Human Action Recognition in Assembly—0
Fusing multiple features for depth-based action recognition—0
C3T: Cross-modal Transfer Through Time for Sensor-based Human Activity Recognition—0
FuTH-Net: Fusing Temporal Relations and Holistic Features for Aerial Video Classification—0
Future Aspects in Human Action Recognition: Exploring Emerging Techniques and Ethical Influences—0
GCF-Net: Gated Clip Fusion Network for Video Action Recognition—0
Optimized Skeleton-based Action Recognition via Sparsified Graph Regression—0
Generalized Rank Pooling for Activity Recognition—0
Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data—0
Generating Action-conditioned Prompts for Open-vocabulary Video Action Recognition—0
Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models—0
Generative Multi-View Human Action Recognition—0
Geometric Deep Neural Network Using Rigid and Non-Rigid Transformations for Human Action Recognition—0
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning—0
Global Context-Aware Attention LSTM Networks for 3D Action Recognition—0
Global Temporal Representation based CNNs for Infrared Action Recognition—0
Going Deeper into Action Recognition: A Survey—0
Going Deeper into First-Person Activity Recognition—0
Gradient Boundary Histograms for Action Recognition—0
Gradient Frequency Modulation for Visually Explaining Video Understanding Models—0
Graph Convolutional Module for Temporal Action Localization in Videos—0
Graph Edge Convolutional Neural Networks for Skeleton Based Action Recognition—0
GraSens: A Gabor Residual Anti-aliasing Sensing Framework for Action Recognition using WiFi—0
Group-Skeleton-Based Human Action Recognition in Complex Events—0
Group sparsity and geometry constrained dictionary learning for action recognition from depth maps.—0
GTA: Global Temporal Attention for Video Action Understanding—0
GTM: Gray Temporal Model for Video Recognition—0
HabitAction: A Video Dataset for Human Habitual Behavior Recognition—0
Hand Action Detection from Ego-centric Depth Sequences with Error-correcting Hough Transform—0
Handcrafted Local Features are Convolutional Neural Networks—0
Handcrafted localized phase features for human action recognition—0
Hand-Object Interaction and Precise Localization in Transitive Action Recognition—0
Harnessing Object and Scene Semantics for Large-Scale Video Understanding—0
Harnessing the Deep Net Object Models for Enhancing Human Action Recognition—0
HAUAR: Home Automation Using Action Recognition—0
hear-your-action: human action recognition by ultrasound active sensing—0
Heterogeneous Skeleton-Based Action Representation Learning—0
Hierarchical Attention Network for Action Recognition in Videos—0
Hierarchical Contrastive Motion Learning for Video Action Recognition—0
Hierarchical Feature Aggregation Networks for Video Action Recognition—0
Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition—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