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 251275 of 455 papers

TitleStatusHype
A convex method for classification of groups of examples0
ActionVLAD: Learning spatio-temporal aggregation for action classification0
Active Learning for Video Classification with Frame Level Queries0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction0
RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression0
Aggregating Frame-level Features for Large-Scale Video Classification0
Aligning Correlation Information for Domain Adaptation in Action Recognition0
Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths0
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception0
AM Flow: Adapters for Temporal Processing in Action Recognition0
Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms0
An Effective Way to Improve YouTube-8M Classification Accuracy in Google Cloud Platform0
An Empirical Study of Autoregressive Pre-training from Videos0
An Investigation on Hardware-Aware Vision Transformer Scaling0
Appending Adversarial Frames for Universal Video Attack0
Approach for Video Classification with Multi-label on YouTube-8M Dataset0
A spatiotemporal model with visual attention for video classification0
A Spectral Nonlocal Block for Neural Networks0
A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP0
A Temporal Fusion Approach for Video Classification with Convolutional and LSTM Neural Networks Applied to Violence Detection0
Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API0
Attend and Interact: Higher-Order Object Interactions for Video Understanding0
Attend-Fusion: Efficient Audio-Visual Fusion for Video Classification0
Attention-Aware Noisy Label Learning for Image Classification0
Show:102550
← PrevPage 11 of 19Next →

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