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 176200 of 455 papers

TitleStatusHype
Harnessing Object and Scene Semantics for Large-Scale Video Understanding0
Class Prototypes Based Contrastive Learning for Classifying Multi-Label and Fine-Grained Educational Videos0
Learning Video Representations using Contrastive Bidirectional Transformer0
3D CNN-PCA: A Deep-Learning-Based Parameterization for Complex Geomodels0
Higher-order Network for Action Recognition0
MANIFOLDNET: A DEEP NEURAL NETWORK FOR MANIFOLD-VALUED DATA0
Goal-driven text descriptions for images0
GenVidBench: A Challenging Benchmark for Detecting AI-Generated Video0
Classifying Video based on Automatic Content Detection Overview0
I Have Seen Enough: A Teacher Student Network for Video Classification Using Fewer Frames0
Generating Video Description using Sequence-to-sequence Model with Temporal Attention0
Generating Natural Language Summaries for Multimedia0
Charades-Ego: A Large-Scale Dataset of Paired Third and First Person Videos0
Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification0
Intelligent 3D Network Protocol for Multimedia Data Classification using Deep Learning0
Cascaded Pyramid Mining Network for Weakly Supervised Temporal Action Localization0
ActionVLAD: Learning spatio-temporal aggregation for action classification0
FuTH-Net: Fusing Temporal Relations and Holistic Features for Aerial Video Classification0
Fusing Multi-Stream Deep Networks for Video Classification0
Approach for Video Classification with Multi-label on YouTube-8M Dataset0
LookupViT: Compressing visual information to a limited number of tokens0
Towards Train-Test Consistency for Semi-supervised Temporal Action Localization0
Label Denoising with Large Ensembles of Heterogeneous Neural Networks0
FSD-10: A Dataset for Competitive Sports Content Analysis0
Fine-grained Video Categorization with Redundancy Reduction Attention0
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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