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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 51–75 of 307 papers

TitleStatusHype
MAR: Masked Autoencoders for Efficient Action RecognitionCode1
In Defense of Image Pre-Training for Spatiotemporal RecognitionCode1
Long Movie Clip Classification with State-Space Video ModelsCode1
Group Contextualization for Video RecognitionCode1
Fast Differentiable Matrix Square Root and Inverse Square RootCode1
MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video RecognitionCode1
OCSampler: Compressing Videos to One Clip with Single-step SamplingCode1
Glance and Focus Networks for Dynamic Visual RecognitionCode1
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video RecognitionCode1
DualFormer: Local-Global Stratified Transformer for Efficient Video RecognitionCode1
MViTv2: Improved Multiscale Vision Transformers for Classification and DetectionCode1
Pooling by Sliced-Wasserstein EmbeddingCode1
TokenLearner: Adaptive Space-Time Tokenization for VideosCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
Efficient Video Transformers with Spatial-Temporal Token SelectionCode1
Attacking Video Recognition Models with Bullet-Screen CommentsCode1
Temporal-attentive Covariance Pooling Networks for Video RecognitionCode1
Boosting the Transferability of Video Adversarial Examples via Temporal TranslationCode1
Unsupervised 3D Pose Estimation for Hierarchical Dance Video RecognitionCode1
Dynamic Network Quantization for Efficient Video InferenceCode1
Can An Image Classifier Suffice For Action Recognition?Code1
Towards Long-Form Video UnderstandingCode1
TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?Code1
Self-supervised Video Representation Learning with Cross-Stream Prototypical ContrastingCode1
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in PythonCode1
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