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 901–950 of 1477 papers

TitleStatusHype
Towards Good Practices for Action Video Encoding—0
Towards Improved Human Action Recognition Using Convolutional Neural Networks and Multimodal Fusion of Depth and Inertial Sensor Data—0
Towards Universal Representation for Unseen Action Recognition—0
Tracking Human Pose by Tracking Symmetric Parts—0
Train, Diagnose and Fix: Interpretable Approach for Fine-grained Action Recognition—0
Training for temporal sparsity in deep neural networks, application in video processing—0
Trajectory Aligned Features For First Person Action Recognition—0
Trajectory Convolution for Action Recognition—0
Transductive Zero-Shot Action Recognition by Word-Vector Embedding—0
Transferable Feature Representation for Visible-to-Infrared Cross-Dataset Human Action Recognition—0
Transferable Knowledge-Based Multi-Granularity Aggregation Network for Temporal Action Localization: Submission to ActivityNet Challenge 2021—0
Transformer-based Fusion of 2D-pose and Spatio-temporal Embeddings for Distracted Driver Action Recognition—0
Transition Forests: Learning Discriminative Temporal Transitions for Action Recognition and Detection—0
TransNet: A Transfer Learning-Based Network for Human Action Recognition—0
T-RECS: Training for Rate-Invariant Embeddings by Controlling Speed for Action Recognition—0
Trimmed Action Recognition, Dense-Captioning Events in Videos, and Spatio-temporal Action Localization with Focus on ActivityNet Challenge 2019—0
TSI: Temporal Saliency Integration for Video Action Recognition—0
TUHOI: Trento Universal Human Object Interaction Dataset—0
Two-Stream 3D Convolutional Neural Network for Skeleton-Based Action Recognition—0
Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization—0
Two-Stream Consensus Network: Submission to HACS Challenge 2021 Weakly-Supervised Learning Track—0
Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition—0
Two-stream Multi-level Dynamic Point Transformer for Two-person Interaction Recognition—0
Two-Stream Networks for Lane-Change Prediction of Surrounding Vehicles—0
Two-Stream Networks for Weakly-Supervised Temporal Action Localization With Semantic-Aware Mechanisms—0
Two-Stream RNN/CNN for Action Recognition in 3D Videos—0
Two Stream Self-Supervised Learning for Action Recognition—0
Two-stream Spatiotemporal Feature for Video QA Task—0
UC Merced Submission to the ActivityNet Challenge 2016—0
Unified Contrastive Fusion Transformer for Multimodal Human Action Recognition—0
Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling—0
UnLoc: A Unified Framework for Video Localization Tasks—0
Unrepresentative video data: A review and evaluation—0
Unseen Action Recognition with Unpaired Adversarial Multimodal Learning—0
Unsupervised Action Proposal Ranking through Proposal Recombination—0
Unsupervised Domain Adaptation for Action Recognition via Self-Ensembling and Conditional Embedding Alignment—0
Unsupervised Domain Adaptation for Spatio-Temporal Action Localization—0
Unsupervised Domain Adaptation for Zero-Shot Learning—0
Unsupervised Spectral Dual Assignment Clustering of Human Actions in Context—0
Using joint angles based on the international biomechanical standards for human action recognition and related tasks—0
Variational Conditional Dependence Hidden Markov Models for Skeleton-Based Action Recognition—0
Video action recognition for lane-change classification and prediction of surrounding vehicles—0
Video Action Recognition Using spatio-temporal optical flow video frames—0
Video Action Recognition Via Neural Architecture Searching—0
Video Action Recognition with Attentive Semantic Units—0
Video-Based Action Recognition Using Rate-Invariant Analysis of Covariance Trajectories—0
Video-based Human Action Recognition using Deep Learning: A Review—0
Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention—0
Perceptron Synthesis Network: Rethinking the Action Scale Variances in Videos—0
VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding—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