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 201225 of 455 papers

TitleStatusHype
TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity RecognitionCode0
Efficient Lung Ultrasound Severity Scoring Using Dedicated Feature ExtractorCode0
Analyzing Linear Dynamical Systems: From Modeling to Coding and LearningCode0
Long-term Leap Attention, Short-term Periodic Shift for Video ClassificationCode0
Loss Switching Fusion with Similarity Search for Video ClassificationCode0
Learnable pooling with Context Gating for video classificationCode0
Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video ClassificationCode0
NeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video ClassificationCode0
Efficient Action Localization with Approximately Normalized Fisher Vectors0
AVD: Adversarial Video Distillation0
DynamoNet: Dynamic Action and Motion Network0
Automatic Concept Extraction for Concept Bottleneck-based Video Classification0
Document-Level Sentiment Analysis of Urdu Text Using Deep Learning Techniques0
DL-KDD: Dual-Light Knowledge Distillation for Action Recognition in the Dark0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction0
Distribution Adaptive INT8 Quantization for Training CNNs0
Distributed Deep Convolutional Neural Networks for the Internet-of-Things0
Discriminatively Trained Latent Ordinal Model for Video Classification0
A Unified Method for First and Third Person Action Recognition0
Discrepancy-Aware Attention Network for Enhanced Audio-Visual Zero-Shot Learning0
Linear Video Transformer with Feature Fixation0
AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification0
AM Flow: Adapters for Temporal Processing in Action Recognition0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction0
Leveraging Compressed Frame Sizes For Ultra-Fast Video Classification0
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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