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 426450 of 455 papers

TitleStatusHype
Selective Structured State-Spaces for Long-Form Video Understanding0
Self-Paced Video Data Augmentation with Dynamic Images Generated by Generative Adversarial Networks0
Self-Supervised Multi-Task Procedure Learning from Instructional Videos0
Self-supervised Temporal Learning0
Semantic Adversarial Network with Multi-scale Pyramid Attention for Video Classification0
Semi-supervised and Deep learning Frameworks for Video Classification and Key-frame Identification0
Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model0
Shuffle to Learn: Self-supervised learning from permutations via differentiable ranking0
Smoothed Gaussian Mixture Models for Video Classification and Recommendation0
SOS! Self-supervised Learning Over Sets Of Handled Objects In Egocentric Action Recognition0
Sparse Coding and Dictionary Learning With Linear Dynamical Systems0
Spatiotemporal Analysis of Forest Machine Operations Using 3D Video Classification0
Spatio-Temporal Fusion Networks for Action Recognition0
Spatiotemporal Learning with Context-aware Video Tubelets for Ultrasound Video Analysis0
Spectral Nonlocal Block for Neural Network0
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition0
TAEN: Temporal Aware Embedding Network for Few-Shot Action Recognition0
PatchZero: Defending against Adversarial Patch Attacks by Detecting and Zeroing the Patch0
Technical Report: Disentangled Action Parsing Networks for Accurate Part-level Action Parsing0
Temporal Alignment Prediction for Few-Shot Video Classification0
Temporal Bilinear Encoding Network of Audio-Visual Features at Low Sampling Rates0
Temporal Coherent Test-Time Optimization for Robust Video Classification0
TenAd: A Tensor-based Low-rank Black Box Adversarial Attack for Video Classification0
t-EVA: Time-Efficient t-SNE Video Annotation0
P2ANet: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos0
Show:102550
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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