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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 201–225 of 307 papers

TitleStatusHype
Annotation-Efficient Untrimmed Video Action Recognition—0
11 TeraFLOPs per second photonic convolutional accelerator for deep learning optical neural networks—0
PV-NAS: Practical Neural Architecture Search for Video Recognition—0
Depth Guided Adaptive Meta-Fusion Network for Few-shot Video RecognitionCode1
Dissected 3D CNNs: Temporal Skip Connections for Efficient Online Video ProcessingCode1
MultAV: Multiplicative Adversarial Videos—0
Defending Against Multiple and Unforeseen Adversarial Videos—0
Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs—0
Learning Temporally Invariant and Localizable Features via Data Augmentation for Video RecognitionCode1
Self-supervised Video Representation Learning Using Inter-intra Contrastive FrameworkCode1
Fast Approximate Modelling of the Next Combination Result for Stopping the Text Recognition in a VideoCode0
RubiksNet: Learnable 3D-Shift for Efficient Video Action RecognitionCode1
Adversarial Bipartite Graph Learning for Video Domain AdaptationCode1
Generalized Few-Shot Video Classification with Video Retrieval and Feature GenerationCode1
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual RecognitionCode1
Video Panoptic SegmentationCode1
0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event CameraCode1
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition—0
TAM: Temporal Adaptive Module for Video RecognitionCode1
Compositional Few-Shot Recognition with Primitive Discovery and Enhancing—0
V4D: 4D Convolutional Neural Networks for Video-level Representation Learning—0
CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture RecognitionCode1
DriftNet: Aggressive Driving Behavior Classification using 3D EfficientNet ArchitectureCode0
Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?Code2
Improved Residual Networks for Image and Video RecognitionCode1
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