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 201250 of 455 papers

TitleStatusHype
Evaluation of Explanation Methods of AI -- CNNs in Image Classification Tasks with Reference-based and No-reference MetricsCode0
Deep Multimodality Learning for UAV Video Aesthetic Quality AssessmentCode0
Identifying Misinformation on YouTube through Transcript Contextual Analysis with Transformer ModelsCode0
SIAVC: Semi-Supervised Framework for Industrial Accident Video ClassificationCode0
Multi-modality transrectal ultrasound video classification for identification of clinically significant prostate cancerCode0
Movie Genre Classification by Language Augmentation and Shot SamplingCode0
Long-term Leap Attention, Short-term Periodic Shift for Video ClassificationCode0
Deep RNN Framework for Visual Sequential ApplicationsCode0
ActAlign: Zero-Shot Fine-Grained Video Classification via Language-Guided Sequence AlignmentCode0
Towards Good Practices for Multi-modal Fusion in Large-scale Video Classification0
Towards Zero-Shot & Explainable Video Description by Reasoning over Graphs of Events in Space and Time0
ToxVidLM: A Multimodal Framework for Toxicity Detection in Code-Mixed Videos0
Traffic Congestion Prediction using Deep Convolutional Neural Networks: A Color-coding Approach0
Transfer-learning for video classification: Video Swin Transformer on multiple domains0
Transformers Meet Visual Learning Understanding: A Comprehensive Review0
Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos0
Two-stream Collaborative Learning with Spatial-Temporal Attention for Video Classification0
Two-stream Convolutional Networks for Multi-frame Face Anti-spoofing0
Two-Stream Transformer Architecture for Long Video Understanding0
Two-Stream Video Classification with Cross-Modality Attention0
UAV-CROWD: Violent and non-violent crowd activity simulator from the perspective of UAV0
Unbiasing through Textual Descriptions: Mitigating Representation Bias in Video Benchmarks0
Uncertainty-Aware Weakly Supervised Action Detection from Untrimmed Videos0
Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling0
UniForensics: Face Forgery Detection via General Facial Representation0
UNIVERSAL MODAL EMBEDDING OF DYNAMICS IN VIDEOS AND ITS APPLICATIONS0
Unsupervised Action Localization Crop in Video Retargeting for 3D ConvNets0
SSCAP: Self-supervised Co-occurrence Action Parsing for Unsupervised Temporal Action Segmentation0
Unsupervised Meta-Learning For Few-Shot Image Classification0
Variable-frame CNNLSTM for Breast Nodule Classification using Ultrasound Videos0
Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks0
Video-Based Action Recognition Using Rate-Invariant Analysis of Covariance Trajectories0
Video Classification using Semantic Concept Co-occurrences0
Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor0
Video Contents Understanding using Deep Neural Networks0
VideoGraph: Recognizing Minutes-Long Human Activities in Videos0
VideoSSL: Semi-Supervised Learning for Video Classification0
VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners0
Video Token Merging for Long-form Video Understanding0
Video Understanding as Machine Translation0
VidTr: Video Transformer Without Convolutions0
Visual Data Synthesis via GAN for Zero-Shot Video Classification0
Walk-Steered Convolution for Graph Classification0
When Video Classification Meets Incremental Classes0
Where and when to look? Spatial-temporal attention for action recognition in videos0
DASZL: Dynamic Action Signatures for Zero-shot Learning0
Optimizing Temporal Convolutional Network inference on FPGA-based accelerators0
3D CNN-PCA: A Deep-Learning-Based Parameterization for Complex Geomodels0
Accurate and Efficient Two-Stage Gun Detection in Video0
A convex method for classification of groups of examples0
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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