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Video Recognition

Video Recognition is a process of obtaining, processing, and analysing data that it receives from a visual source, specifically video.

Papers

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Showing 151–175 of 307 papers

TitleStatusHype
GTM: Gray Temporal Model for Video Recognition—0
Boosting the Transferability of Video Adversarial Examples via Temporal TranslationCode1
TSM: Temporal Shift Module for Efficient and Scalable Video Understanding on Edge DeviceCode2
QTTNet: Quantized Tensor Train Neural Networks for 3D Object and Video Recognition.Code0
Unsupervised 3D Pose Estimation for Hierarchical Dance Video RecognitionCode1
Large-vocabulary Audio-visual Speech Recognition in Noisy Environments—0
Revisiting 3D ResNets for Video RecognitionCode0
Towards Learning a Vocabulary of Visual Concepts and Operators using Deep Neural Networks—0
Searching for Two-Stream Models in Multivariate Space for Video Recognition—0
Reinforcement Learning Based Sparse Black-box Adversarial Attack on Video Recognition Models—0
Dynamic Network Quantization for Efficient Video InferenceCode1
Towards Efficient Tensor Decomposition-Based DNN Model Compression with Optimization Framework—0
Inter-intra Variant Dual Representations forSelf-supervised Video RecognitionCode0
Can An Image Classifier Suffice For Action Recognition?Code1
Video Swin TransformerCode2
TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?Code1
Towards Long-Form Video UnderstandingCode1
Self-supervised Video Representation Learning with Cross-Stream Prototypical ContrastingCode1
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in PythonCode1
VidHarm: A Clip Based Dataset for Harmful Content Detection—0
Space-time Mixing Attention for Video TransformerCode1
Continual 3D Convolutional Neural Networks for Real-time Processing of VideosCode1
DSANet: Dynamic Segment Aggregation Network for Video-Level Representation LearningCode1
Sharing Pain: Using Pain Domain Transfer for Video Recognition of Low Grade Orthopedic Pain in HorsesCode1
AdaMML: Adaptive Multi-Modal Learning for Efficient Video RecognitionCode1
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