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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
2D or not 2D? Adaptive 3D Convolution Selection for Efficient Video Recognition—0
Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition—0
Maximum A Posteriori Estimation of Distances Between Deep Features in Still-to-Video Face Recognition—0
MeMSVD: Long-Range Temporal Structure Capturing Using Incremental SVD—0
The Influence of Audio on Video Memorability with an Audio Gestalt Regulated Video Memorability System—0
Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain—0
M&M Mix: A Multimodal Multiview Transformer Ensemble—0
Modeling Sub-Event Dynamics in First-Person Action Recognition—0
Morph: Flexible Acceleration for 3D CNN-based Video Understanding—0
Motion-Augmented Self-Training for Video Recognition at Smaller Scale—0
Motion Guided Token Compression for Efficient Masked Video Modeling—0
Video Mobile-Former: Video Recognition with Efficient Global Spatial-temporal Modeling—0
MRET: Multi-resolution Transformer for Video Quality Assessment—0
MultAV: Multiplicative Adversarial Videos—0
Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition—0
Multi-Fiber Networks for Video Recognition—0
Multi Modal Convolutional Neural Networks for Brain Tumor Segmentation—0
Multimodal Transfer Deep Learning with Applications in Audio-Visual Recognition—0
Multi-object Video Generation from Single Frame Layouts—0
Multiview Pseudo-Labeling for Semi-supervised Learning from Video—0
Noise-Tolerant Learning for Audio-Visual Action Recognition—0
Non-local NetVLAD Encoding for Video Classification—0
Towards Efficient Tensor Decomposition-Based DNN Model Compression with Optimization Framework—0
NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition—0
Towards Extremely Compact RNNs for Video Recognition with Fully Decomposed Hierarchical Tucker Structure—0
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