SOTAVerified

Video Classification

Video Classification is the task of producing a label that is relevant to the video given its frames. A good video level classifier is one that not only provides accurate frame labels, but also best describes the entire video given the features and the annotations of the various frames in the video. For example, a video might contain a tree in some frame, but the label that is central to the video might be something else (e.g., “hiking”). The granularity of the labels that are needed to describe the frames and the video depends on the task. Typical tasks include assigning one or more global labels to the video, and assigning one or more labels for each frame inside the video.

Source: Efficient Large Scale Video Classification

Papers

Showing 351375 of 455 papers

TitleStatusHype
Higher-order Network for Action Recognition0
Identifying and Resisting Adversarial Videos Using Temporal Consistency0
I Have Seen Enough: A Teacher Student Network for Video Classification Using Fewer Frames0
Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning0
Intelligent 3D Network Protocol for Multimedia Data Classification using Deep Learning0
IntFormer: Predicting pedestrian intention with the aid of the Transformer architecture0
iqiyi Submission to ActivityNet Challenge 2019 Kinetics-700 challenge: Hierarchical Group-wise Attention0
Isometric Transformation Invariant Graph-based Deep Neural Network0
Label Denoising with Large Ensembles of Heterogeneous Neural Networks0
Labeling the Features Not the Samples: Efficient Video Classification with Minimal Supervision0
Language as the Medium: Multimodal Video Classification through text only0
Large-scale Video Classification guided by Batch Normalized LSTM Translator0
Large-Scale Video Classification with Feature Space Augmentation coupled with Learned Label Relations and Ensembling0
Large-Scale YouTube-8M Video Understanding with Deep Neural Networks0
Learning Correlation Structures for Vision Transformers0
Learning Expressive And Generalizable Motion Features For Face Forgery Detection0
Learning Muti-expert Distribution Calibration for Long-tailed Video Classification0
Learning Natural Consistency Representation for Face Forgery Video Detection0
Learning Representative Temporal Features for Action Recognition0
Learning spatio-temporal representations with temporal squeeze pooling0
Leveraging Compressed Frame Sizes For Ultra-Fast Video Classification0
Linear Video Transformer with Feature Fixation0
Long-short Term Motion Feature for Action Classification and Retrieval0
LookupViT: Compressing visual information to a limited number of tokens0
Towards Train-Test Consistency for Semi-supervised Temporal Action Localization0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HERMESAccuracy (%)95.2Unverified
2MA-LMMAccuracy (%)93Unverified
3S5Accuracy (%)90.7Unverified
4TranS4merAccuracy (%)90.27Unverified
5D-Sprv.Accuracy (%)89.9Unverified
6ViS4merAccuracy (%)88.2Unverified
7GHRMAccuracy (%)75.5Unverified
8TimeceptionAccuracy (%)71.3Unverified
9VideoGraphAccuracy (%)69.5Unverified
#ModelMetricClaimedVerifiedStatus
1HERMESAccuracy (%)93.5Unverified
2MA-LMMAccuracy (%)93.2Unverified
3S5Accuracy (%)90.8Unverified
4D-Sprv.Accuracy (%)90Unverified
5TranS4merAccuracy (%)89.3Unverified
6ViS4merAccuracy (%)88.4Unverified
7TSNAccuracy (%)73.4Unverified
#ModelMetricClaimedVerifiedStatus
1VTNAccuracy77.85Unverified
2I3DAccuracy72.11Unverified
3ConvLSTMAccuracy69.71Unverified
#ModelMetricClaimedVerifiedStatus
1DCGN (self-attention graph pooling)Hit@187.7Unverified
2Hierarchical LSTM with MoEHit@186.8Unverified
3Mixture-of-2-ExpertsHit@170.1Unverified
#ModelMetricClaimedVerifiedStatus
1Structured Keypoint PoolingAccuracy99.5Unverified
2CNN+LSTM1:1 Accuracy98Unverified
#ModelMetricClaimedVerifiedStatus
1MultigridmAP38.2Unverified
#ModelMetricClaimedVerifiedStatus
1Cooperative Ours (3rd-person)Accuracy (%)24.7Unverified
#ModelMetricClaimedVerifiedStatus
1MultigridTop-177.6Unverified
#ModelMetricClaimedVerifiedStatus
1VideoAccuracy (%)73.95Unverified
#ModelMetricClaimedVerifiedStatus
1MSNet-R50En (ours)Top-5 Accuracy84Unverified
#ModelMetricClaimedVerifiedStatus
1MSNet-R50En (ours)Top-5 Accuracy91Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Label Prototypes Contrastive LearningAUPR88.4Unverified