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 701–750 of 1477 papers

TitleStatusHype
RNNs, CNNs and Transformers in Human Action Recognition: A Survey and a Hybrid Model—0
Robust 3D Action Recognition through Sampling Local Appearances and Global Distributions—0
Robust Estimation of 3D Human Poses from a Single Image—0
Robust features for facial action recognition—0
Robust Multi-body Feature Tracker: A Segmentation-free Approach—0
Robust Statistical Approach for Extraction of Moving Human Silhouettes from Videos—0
Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data—0
RSA: Randomized Simulation as Augmentation for Robust Human Action Recognition—0
R-STAN: Residual Spatial-Temporal Attention Network for Action Recognition—0
SAIC_Cambridge-HuPBA-FBK Submission to the EPIC-Kitchens-100 Action Recognition Challenge 2021—0
Sampling Strategies for Real-Time Action Recognition—0
What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition—0
Scalable and Compact 3D Action Recognition with Approximated RBF Kernel Machines—0
Scale Coding Bag of Deep Features for Human Attribute and Action Recognition—0
Scale Matters: Temporal Scale Aggregation Network for Precise Action Localization in Untrimmed Videos—0
Scene Flow to Action Map: A New Representation for RGB-D based Action Recognition with Convolutional Neural Networks—0
Scenes-Objects-Actions: A Multi-Task, Multi-Label Video Dataset—0
SCSampler: Sampling Salient Clips from Video for Efficient Action Recognition—0
MM-SEAL: A Large-scale Video Dataset of Multi-person Multi-grained Spatio-temporally Action Localization—0
Second-order Temporal Pooling for Action Recognition—0
Seeing What You're Told: Sentence-Guided Activity Recognition In Video—0
Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation—0
Self-Attention Network for Skeleton-based Human Action Recognition—0
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization—0
Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment—0
Self-Supervised Spatiotemporal Feature Learning via Video Rotation Prediction—0
Self-Supervised Spatiotemporal Learning via Video Clip Order Prediction—0
Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles—0
Self-Supervised Video Representation Learning With Odd-One-Out Networks—0
Self-Supervised Video Representation Learning with Meta-Contrastive Network—0
Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks—0
Semantic Embedding Space for Zero-Shot Action Recognition—0
Semantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition—0
Semantic Image Networks for Human Action Recognition—0
Semantic Labeling of Human Action For Visually Impaired And Blind People Scene Interaction—0
Semi-Coupled Two-Stream Fusion ConvNets for Action Recognition at Extremely Low Resolutions—0
Semi-Supervised Audio-Visual Video Action Recognition with Audio Source Localization Guided Mixup—0
Semi-supervised Fisher vector network—0
Semi-Supervised Pipe Video Temporal Defect Interval Localization—0
Sequence Summarization Using Order-constrained Kernelized Feature Subspaces—0
Sequential Deep Trajectory Descriptor for Action Recognition with Three-stream CNN—0
Shrinkage Optimized Directed Information using Pictorial Structures for Action Recognition—0
Shuffle and Attend: Video Domain Adaptation—0
Shuffle and Learn: Unsupervised Learning using Temporal Order Verification—0
Signal Alignment for Humanoid Skeletons via the Globally Optimal Reparameterization Algorithm—0
Similarity Min-Max: Zero-Shot Day-Night Domain Adaptation—0
Simplex-Based 3D Spatio-Temporal Feature Description for Action Recognition—0
Single Image Action Recognition by Predicting Space-Time Saliency—0
Single Image Action Recognition using Semantic Body Part Actions—0
SITAR: Semi-supervised Image Transformer for Action 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