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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
CA^2ST: Cross-Attention in Audio, Space, and Time for Holistic Video Recognition—0
Reinforcement Learning Based Sparse Black-box Adversarial Attack on Video Recognition Models—0
REST: REtrieve & Self-Train for generative action recognition—0
Class-Incremental Learning for Action Recognition in Videos—0
Video Task Decathlon: Unifying Image and Video Tasks in Autonomous Driving—0
Retro-Actions: Learning 'Close' by Time-Reversing 'Open' Videos—0
Multi-Task Learning of Generalizable Representations for Video Action Recognition—0
Compositional Few-Shot Recognition with Primitive Discovery and Enhancing—0
Condensing a Sequence to One Informative Frame for Video Recognition—0
Convolutional Neural Network on Three Orthogonal Planes for Dynamic Texture Classification—0
Correlation Net: Spatiotemporal multimodal deep learning for action recognition—0
Cross-Block Fine-Grained Semantic Cascade for Skeleton-Based Sports Action Recognition—0
Cross-Modal Transferable Adversarial Attacks from Images to Videos—0
DAVE: Diverse Atomic Visual Elements Dataset with High Representation of Vulnerable Road Users in Complex and Unpredictable Environments—0
DeepGamble: Towards unlocking real-time player intelligence using multi-layer instance segmentation and attribute detection—0
Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled—0
Deep Networks With Large Output Spaces—0
Defending Against Multiple and Unforeseen Adversarial Videos—0
A Novel Audio-Visual Information Fusion System for Mental Disorders Detection—0
Demonstration of Vector Flow Imaging using Convolutional Neural Networks—0
Revisiting the Effectiveness of Off-the-shelf Temporal Modeling Approaches for Large-scale Video Classification—0
Design Light-weight 3D Convolutional Networks for Video Recognition Temporal Residual, Fully Separable Block, and Fast Algorithm—0
V4D: 4D Convolutional Neural Networks for Video-level Representation Learning—0
AdaFrame: Adaptive Frame Selection for Fast Video Recognition—0
Searching for Two-Stream Models in Multivariate Space for Video Recognition—0
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