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 5175 of 455 papers

TitleStatusHype
Is normalization indispensable for training deep neural network?Code1
Overlooked Video Classification in Weakly Supervised Video Anomaly DetectionCode1
Billion-scale semi-supervised learning for image classificationCode1
Over-the-Air Adversarial Flickering Attacks against Video Recognition NetworksCode1
Attention in Attention: Modeling Context Correlation for Efficient Video ClassificationCode1
A Closer Look at Few-Shot Video Classification: A New Baseline and BenchmarkCode1
A Multigrid Method for Efficiently Training Video ModelsCode1
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained EnvironmentsCode1
A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion RecognitionCode1
A Unified Taxonomy and Multimodal Dataset for Events in Invasion GamesCode1
Reversible Vision TransformersCode1
Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based ApproachCode1
Inductive and Transductive Few-Shot Video Classification via Appearance and Temporal AlignmentsCode1
Learning Implicit Temporal Alignment for Few-shot Video ClassificationCode1
HERMES: temporal-coHERent long-forM understanding with Episodes and SemanticsCode1
HateMM: A Multi-Modal Dataset for Hate Video ClassificationCode1
Exploring Fine-Grained Audiovisual Categorization with the SSW60 DatasetCode1
A Dataset for Medical Instructional Video Classification and Question AnsweringCode1
Generalized Few-Shot Video Classification with Video Retrieval and Feature GenerationCode1
Large Scale Holistic Video UnderstandingCode1
Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video ClassificationCode1
MViTv2: Improved Multiscale Vision Transformers for Classification and DetectionCode1
InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic TasksCode1
EEG-based Emotional Video Classification via Learning Connectivity StructureCode1
ViViT: A Video Vision TransformerCode1
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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