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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 201–250 of 307 papers

TitleStatusHype
GTM: Gray Temporal Model for Video Recognition—0
QTTNet: Quantized Tensor Train Neural Networks for 3D Object and Video Recognition.Code0
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
Towards Efficient Tensor Decomposition-Based DNN Model Compression with Optimization Framework—0
Inter-intra Variant Dual Representations forSelf-supervised Video RecognitionCode0
VidHarm: A Clip Based Dataset for Harmful Content Detection—0
Motion-Augmented Self-Training for Video Recognition at Smaller Scale—0
The Influence of Audio on Video Memorability with an Audio Gestalt Regulated Video Memorability System—0
HCMS: Hierarchical and Conditional Modality Selection for Efficient Video Recognition—0
Towards Extremely Compact RNNs for Video Recognition with Fully Decomposed Hierarchical Tucker Structure—0
On the Pitfalls of Learning with Limited Data: A Facial Expression Recognition Case Study—0
Multiview Pseudo-Labeling for Semi-supervised Learning from Video—0
Recognizing Actions in Videos from Unseen Viewpoints—0
Video Transformer NetworkCode0
Multi-Modal Multi-Action Video RecognitionCode0
Interactive Prototype Learning for Egocentric Action Recognition—0
2D or not 2D? Adaptive 3D Convolution Selection for Efficient Video Recognition—0
DeepGamble: Towards unlocking real-time player intelligence using multi-layer instance segmentation and attribute detection—0
Overcomplete Representations Against Adversarial VideosCode0
Open-Ended Multi-Modal Relational Reasoning for Video Question AnsweringCode0
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
MultAV: Multiplicative Adversarial Videos—0
Defending Against Multiple and Unforeseen Adversarial Videos—0
Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs—0
Fast Approximate Modelling of the Next Combination Result for Stopping the Text Recognition in a VideoCode0
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition—0
Compositional Few-Shot Recognition with Primitive Discovery and Enhancing—0
V4D: 4D Convolutional Neural Networks for Video-level Representation Learning—0
DriftNet: Aggressive Driving Behavior Classification using 3D EfficientNet ArchitectureCode0
BosphorusSign22k Sign Language Recognition Dataset—0
Symbiotic Attention with Privileged Information for Egocentric Action Recognition—0
Audiovisual SlowFast Networks for Video RecognitionCode0
Sparse Black-box Video Attack with Reinforcement LearningCode0
Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition—0
LiteEval: A Coarse-to-Fine Framework for Resource Efficient Video Recognition—0
Learning Efficient Video Representation with Video Shuffle Networks—0
TEINet: Towards an Efficient Architecture for Video Recognition—0
Heuristic Black-box Adversarial Attacks on Video Recognition ModelsCode0
Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain—0
Coverage Guided Testing for Recurrent Neural NetworksCode0
Learning to Localize Temporal Events in Large-scale Video DataCode0
Training Kinetics in 15 Minutes: Large-scale Distributed Training on VideosCode0
A Video Recognition Method by using Adaptive Structural Learning of Long Short Term Memory based Deep Belief Network—0
Scheduled Differentiable Architecture Search for Visual Recognition—0
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