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 376400 of 455 papers

TitleStatusHype
Video-based surgical skill assessment using 3D convolutional neural networksCode0
TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity RecognitionCode0
Actor-Action Video Classification CSC 249/449 Spring 2020 Challenge ReportCode0
Two-Stream Convolutional Networks for Action Recognition in VideosCode0
MASTAF: A Model-Agnostic Spatio-Temporal Attention Fusion Network for Few-shot Video ClassificationCode0
Learnable pooling with Context Gating for video classificationCode0
Learnable Pooling Methods for Video ClassificationCode0
Video action detection by learning graph-based spatio-temporal interactionsCode0
Structured Label Inference for Visual UnderstandingCode0
Deep Multimodality Learning for UAV Video Aesthetic Quality AssessmentCode0
NeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video ClassificationCode0
NLP-based Feature Extraction for the Detection of COVID-19 Misinformation Videos on YouTubeCode0
Video Classification with Channel-Separated Convolutional NetworksCode0
Inflated 3D Convolution-Transformer for Weakly-supervised Carotid Stenosis Grading with Ultrasound VideosCode0
Identifying Misinformation on YouTube through Transcript Contextual Analysis with Transformer ModelsCode0
Deep Learning for Video Classification and CaptioningCode0
OccludeNet: A Causal Journey into Mixed-View Actor-Centric Video Action Recognition under OcclusionsCode0
Adaptive occlusion sensitivity analysis for visually explaining video recognition networksCode0
Analyzing Linear Dynamical Systems: From Modeling to Coding and LearningCode0
ViC-MAE: Self-Supervised Representation Learning from Images and Video with Contrastive Masked AutoencodersCode0
Hierarchical Deep Recurrent Architecture for Video UnderstandingCode0
CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016Code0
Ultrasound Image-to-Video Synthesis via Latent Dynamic Diffusion ModelsCode0
Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action RecognitionCode0
Analysis and Extensions of Adversarial Training for Video ClassificationCode0
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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