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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 151–200 of 307 papers

TitleStatusHype
Annotation-Efficient Untrimmed Video Action Recognition—0
Early Detection of Injuries in MLB Pitchers from Video—0
Efficient Attention-free Video Shift Transformers—0
Efficient Decision-based Black-box Patch Attacks on Video Recognition—0
View while Moving: Efficient Video Recognition in Long-untrimmed Videos—0
Efficient Selective Audio Masked Multimodal Bottleneck Transformer for Audio-Video Classification—0
Enhanced Multimodal Representation Learning with Cross-modal KD—0
Enhance Visual Recognition under Adverse Conditions via Deep Networks—0
EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2022: Team HNU-FPV Technical Report—0
Alignment Distances on Systems of Bags—0
Explainable Deep Learning for Video Recognition Tasks: A Framework & Recommendations—0
Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks—0
Exploring Temporally Dynamic Data Augmentation for Video Recognition—0
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos—0
Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks—0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning—0
Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition—0
FlowGraph2Text: Automatic Sentence Skeleton Compilation for Procedural Text Generation—0
Spatiotemporal Attention-based Semantic Compression for Real-time Video Recognition—0
Gameplay Highlights Generation—0
Generating Videos with Scene Dynamics—0
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning—0
Standardization Trends on Safety and Trustworthiness Technology for Advanced AI—0
Video Action Recognition with Attentive Semantic Units—0
Symbiotic Attention with Privileged Information for Egocentric Action Recognition—0
Hierarchical Action Recognition: A Contrastive Video-Language Approach with Hierarchical Interactions—0
Higher-order Network for Action Recognition—0
HCMS: Hierarchical and Conditional Modality Selection for Efficient Video Recognition—0
Image and Video Mining through Online Learning—0
Teaching Machines to Understand Baseball Games: Large-Scale Baseball Video Database for Multiple Video Understanding Tasks—0
TEINet: Towards an Efficient Architecture for Video Recognition—0
Improving Video Model Transfer With Dynamic Representation Learning—0
Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition—0
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition—0
Interactive Prototype Learning for Egocentric Action Recognition—0
Inter-frame Accelerate Attack against Video Interpolation Models—0
Algorithm and Hardware Co-Design of Energy-Efficient LSTM Networks for Video Recognition with Hierarchical Tucker Tensor Decomposition—0
Is an Object-Centric Video Representation Beneficial for Transfer?—0
VidHarm: A Clip Based Dataset for Harmful Content Detection—0
Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs—0
Large-scale Video Classification guided by Batch Normalized LSTM Translator—0
Large-vocabulary Audio-visual Speech Recognition in Noisy Environments—0
Contrastive Video Representation Learning via Adversarial Perturbations—0
Learning Discriminative Video Representations Using Adversarial Perturbations—0
Learning Effective RGB-D Representations for Scene Recognition—0
Learning Efficient Video Representation with Video Shuffle Networks—0
Temporal-Distributed Backdoor Attack Against Video Based Action Recognition—0
Temporal Saliency Query Network for Efficient Video Recognition—0
Leveraging LLMs with Iterative Loop Structure for Enhanced Social Intelligence in Video Question Answering—0
LiteEval: A Coarse-to-Fine Framework for Resource Efficient Video Recognition—0
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