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A Generative Approach to Zero-Shot and Few-Shot Action Recognition
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-46475-6_22openalex-snapshot
Multi-Task Zero-Shot Action Recognition with Prioritised Data Augmentation
inferredcites →https://doi.org/10.1007/978-3-319-50077-5_2openalex-snapshot
An Embarrassingly Simple Approach to Zero-Shot Learning
inferredcites →https://doi.org/10.1007/978-3-319-71246-8_48openalex-snapshot
A Simple Exponential Family Framework for Zero-Shot Learning
inferredcites →https://doi.org/10.1007/s11263-016-0983-5openalex-snapshot
Transductive Zero-Shot Action Recognition by Word-Vector Embedding
inferredcites →https://doi.org/10.1007/s11263-017-1027-5openalex-snapshot
Zero-Shot Visual Recognition via Bidirectional Latent Embedding
inferredcites →https://doi.org/10.1016/j.image.2018.09.003openalex-snapshot
TS-LSTM and temporal-inception: Exploiting spatiotemporal dynamics for activity recognition
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvpr.2005.177openalex-snapshot
Histograms of Oriented Gradients for Human Detection
inferredcites →https://doi.org/10.1109/cvpr.2009.5206594openalex-snapshot
Learning to detect unseen object classes by between-class attribute transfer
inferredcites →https://doi.org/10.1109/cvpr.2009.5206821openalex-snapshot
Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions
inferredcites →https://doi.org/10.1109/cvpr.2011.5995353openalex-snapshot
Recognizing human actions by attributes
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2015.7298911openalex-snapshot
Evaluation of output embeddings for fine-grained image classification
inferredcites →https://doi.org/10.1109/cvpr.2017.117openalex-snapshot
Zero-Shot Action Recognition with Error-Correcting Output Codes
inferredcites →https://doi.org/10.1109/cvpr.2017.473openalex-snapshot
Semantic Autoencoder for Zero-Shot Learning
inferredcites →https://doi.org/10.1109/cvprw.2009.5206594openalex-snapshot
Learning to detect unseen object classes by between-class attribute transfer
inferredcites →https://doi.org/10.1109/iccv.2011.6126543openalex-snapshot
HMDB: A large video database for human motion recognition
inferredcites →https://doi.org/10.1109/iccv.2013.441openalex-snapshot
Action Recognition with Improved Trajectories
inferredcites →https://doi.org/10.1109/iccv.2015.282openalex-snapshot
Unsupervised Domain Adaptation for Zero-Shot Learning
inferredcites →https://doi.org/10.1109/iccv.2015.510openalex-snapshot
Learning Spatiotemporal Features with 3D Convolutional Networks
inferredcites →https://doi.org/10.1109/icip.2015.7350760openalex-snapshot
Semantic embedding space for zero-shot action recognition
inferredcites →https://doi.org/10.1109/tpami.2012.59openalex-snapshot
3D Convolutional Neural Networks for Human Action Recognition
inferredcites →https://doi.org/10.1109/tpami.2013.140openalex-snapshot
Attribute-Based Classification for Zero-Shot Visual Object Categorization
inferredcites →https://doi.org/10.1137/0116083openalex-snapshot
Solution of the Equation $AX + XB = C$ by Inversion of an $M \times M$ or $N \times N$ Matrix
inferredcites →https://doi.org/10.1609/aaai.v32i1.11600openalex-snapshot
Zero-Shot Learning via Class-Conditioned Deep Generative Models
inferredcites →https://doi.org/10.48550/arxiv.1212.0402openalex-snapshot
UCF-101: A dataset of 101 human actions classes from videos in the wild
inferredcites →https://doi.org/10.48550/arxiv.1312.5650openalex-snapshot
Zero-Shot Learning by Convex Combination of Semantic Embeddings
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Action Recognition in Untrimmed Videos with Composite Self-attention Two-Stream Framework
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Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification
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Few-Shot Action Recognition with Permutation-Invariant Attention
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CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition
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Learning Using Privileged Information for Zero-Shot Action Recognition
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Object Priors for Classifying and Localizing Unseen Actions
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Going Deeper into Recognizing Actions in Dark Environments: A Comprehensive Benchmark Study
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Matching Compound Prototypes for Few-Shot Action Recognition
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Hierarchical Motion Excitation Network for Few-Shot Video Recognition
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Zero-Shot Action Recognition with Three-Stream Graph Convolutional Networks
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Cross-modal Hallucination for Few-shot Fine-grained Recognition
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Similarity R-C3D for Few-shot Temporal Activity Detection
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Federated AI lets a team imagine together: Federated Learning of GANs
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TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition
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Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space
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SAFCAR: Structured Attention Fusion for Compositional Action Recognition
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GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognition
inferred← citeshttps://doi.org/10.48550/arxiv.2108.08990openalex-snapshot
Few Shot Activity Recognition Using Variational Inference
inferred← citeshttps://doi.org/10.48550/arxiv.2108.10059openalex-snapshot
ZS-SLR: Zero-Shot Sign Language Recognition from RGB-D Videos
inferred← citeshttps://doi.org/10.48550/arxiv.2109.00796openalex-snapshot
Multi-Modal Zero-Shot Sign Language Recognition
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