Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning | Paper Citation Record

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This paper cites Zero-shot learning through cross-modal transfer,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero-shot learning through cross-modal transfer,

Reference 1

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Observation 21ffba12-783a-4d50-986a-e45ad23a1b84 · outbound

This paper cites An empirical study and analysis of generalized zero-shot learning for object recognition in the wild,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning An empirical study and analysis of generalized zero-shot learning for object recognition in the wild,

Reference 2

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This paper cites Toward open set recognition,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Toward open set recognition,

Reference 3

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This paper cites Probability models for open set recognition,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Probability models for open set recognition,

Reference 4

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This paper cites Robust classiﬁcation with convolutional prototype learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Robust classiﬁcation with convolutional prototype learning,

Reference 5

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This paper cites Recent Advances in Open Set Recognition: A Survey.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Recent Advances in Open Set Recognition: A Survey

Reference 6

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This paper cites Reducing network agnos- tophobia,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Reducing network agnos- tophobia,

Reference 7

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This paper cites C2ae: Class conditioned auto-encoder for open-set recognition,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning C2ae: Class conditioned auto-encoder for open-set recognition,

Reference 8

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This paper cites Triple veriﬁcation network for generalized zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Triple veriﬁcation network for generalized zero-shot learning,

Reference 9

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This paper cites A uniﬁed approach for conventional zero-shot, generalized zero-shot, and few-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning A uniﬁed approach for conventional zero-shot, generalized zero-shot, and few-shot learning,

Reference 10

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Observation 680bb6b9-4cc1-4adb-87f9-331957efa916 · outbound

This paper cites Zero shot learning via low-rank embedded semantic autoencoder.,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero shot learning via low-rank embedded semantic autoencoder.,

Reference 11

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Observation ccf6adad-3a83-42af-a7aa-65aa6ef391b5 · outbound

This paper cites Generalized zero-shot recognition based on visually semantic embedding,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Generalized zero-shot recognition based on visually semantic embedding,

Reference 12

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Observation fadb0678-37ca-4005-a62a-cc7c9da27361 · outbound

This paper cites Generalized zero- shot learning with deep calibration network,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Generalized zero- shot learning with deep calibration network,

Reference 13

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Observation 110a29cd-b5b2-4833-a012-5d0c2fd9dffb · outbound

This paper cites Gener- alized zero-and few-shot learning via aligned variational autoencoders,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Gener- alized zero-and few-shot learning via aligned variational autoencoders,

Reference 14

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Observation 81bf25f7-a939-4f5a-bb09-1a4d88733b6c · outbound

This paper cites Feature generating networks for zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Feature generating networks for zero-shot learning,

Reference 15

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This paper cites Multi-modal cycle- consistent generalized zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Multi-modal cycle- consistent generalized zero-shot learning,

Reference 16

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This paper cites Zero-shot kernel learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero-shot kernel learning,

Reference 17

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Observation d6b3f954-8b0d-48e0-a91a-79be3ca831d9 · outbound

This paper cites NIPS 2016 Tutorial: Generative Adversarial Networks.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning NIPS 2016 Tutorial: Generative Adversarial Networks

Reference 18

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This paper cites Learning to detect unseen object classes by between-class attribute transfer,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Learning to detect unseen object classes by between-class attribute transfer,

Reference 19

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Observation a4ec2b4c-71bd-4302-a6df-2693966eabe4 · outbound

This paper cites Attribute-based classiﬁ- cation for zero-shot visual object categorization,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Attribute-based classiﬁ- cation for zero-shot visual object categorization,

Reference 20

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This paper cites Semi-supervised zero-shot classi- ﬁcation with label representation learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Semi-supervised zero-shot classi- ﬁcation with label representation learning,

Reference 21

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Observation d9873dcc-a9e3-4909-93a8-f2d7e2c122fb · outbound

This paper cites Zero-shot learning-the good, the bad and the ugly,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero-shot learning-the good, the bad and the ugly,

Reference 22

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This paper cites Recent advances in zero-shot recognition: Toward data-efﬁcient understanding of visual content,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Recent advances in zero-shot recognition: Toward data-efﬁcient understanding of visual content,

Reference 23

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Observation fdc03f5c-1f29-4db3-a5c3-bfdd1e167bd6 · outbound

This paper cites Zero-shot learning: An energy based approach,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero-shot learning: An energy based approach,

Reference 24

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This paper cites Learning to share visual appearance for multiclass object detection,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Learning to share visual appearance for multiclass object detection,

Reference 25

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This paper cites Capturing long-tail distribu- tions of object subcategories,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Capturing long-tail distribu- tions of object subcategories,

Reference 26

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This paper cites Zero-shot learning via semantic similarity embedding,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero-shot learning via semantic similarity embedding,

Reference 27

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This paper cites An embarrassingly simple approach to zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning An embarrassingly simple approach to zero-shot learning,

Reference 28

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This paper cites Latent embeddings for zero-shot classiﬁcation,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Latent embeddings for zero-shot classiﬁcation,

Reference 29

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This paper cites Semantic autoencoder for zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Semantic autoencoder for zero-shot learning,

Reference 30

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This paper cites Learning a deep embedding model for zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Learning a deep embedding model for zero-shot learning,

Reference 31

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This paper cites Implicit non-linear similarity scoring for recognizing unseen classes,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Implicit non-linear similarity scoring for recognizing unseen classes,

Reference 32

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This paper cites Zero-shot visual recognition using semantics-preserving adversarial embedding network,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero-shot visual recognition using semantics-preserving adversarial embedding network,

Reference 33

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This paper cites Towards Effective Deep Embedding for Zero-Shot Learning.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Towards Effective Deep Embedding for Zero-Shot Learning

Reference 34

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This paper cites Preserving semantic relations for zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Preserving semantic relations for zero-shot learning,

Reference 35

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This paper cites Dual-veriﬁcation network for zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Dual-veriﬁcation network for zero-shot learning,

Reference 36

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Observation 49eacb5c-0a00-4bac-a4c4-f31e278c122c · outbound

This paper cites Dissimilarity representation learning for generalized zero-shot recognition,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Dissimilarity representation learning for generalized zero-shot recognition,

Reference 37

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Observation 1b0827c9-6b5d-41b5-86d5-70bd53516f5c · outbound

This paper cites Pseudo transfer with marginalized corrupted attribute for zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Pseudo transfer with marginalized corrupted attribute for zero-shot learning,

Reference 38

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This paper cites Generalized zero- shot learning via synthesized examples,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Generalized zero- shot learning via synthesized examples,

Reference 39

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This paper cites Bi-Adversarial Auto-Encoder for Zero-Shot Learning.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Bi-Adversarial Auto-Encoder for Zero-Shot Learning

Reference 40

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This paper cites Leveraging the invariant side of generative zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Leveraging the invariant side of generative zero-shot learning,

Reference 41

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This paper cites Multi-modal ensemble classiﬁcation for generalized zero shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Multi-modal ensemble classiﬁcation for generalized zero shot learning,

Reference 42

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This paper cites Learning the Compositional Spaces for Generalized Zero-shot Learning.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Learning the Compositional Spaces for Generalized Zero-shot Learning

Reference 43

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This paper cites Adaptive conﬁdence smoothing for gen- eralized zero-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Adaptive conﬁdence smoothing for gen- eralized zero-shot learning,

Reference 44

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This paper cites Zero-shot learning- a comprehensive evaluation of the good, the bad and the ugly,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Zero-shot learning- a comprehensive evaluation of the good, the bad and the ugly,

Reference 45

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This paper cites The caltech-ucsd birds-200-2011 dataset,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning The caltech-ucsd birds-200-2011 dataset,

Reference 46

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This paper cites Sun attribute database: Discovering, annotat- ing, and recognizing scene attributes,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Sun attribute database: Discovering, annotat- ing, and recognizing scene attributes,

Reference 47

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Observation c9b86063-e9b0-4904-9d21-778791d42f3f · outbound

This paper cites Describing objects by their attributes,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Describing objects by their attributes,

Reference 48

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Observation 5989f729-2d00-4883-b068-335c774e065a · outbound

This paper cites Deep residual learning for image recognition,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Deep residual learning for image recognition,

Reference 49

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This paper cites Imagenet large scale visual recognition challenge,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Imagenet large scale visual recognition challenge,

Reference 50

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Observation 8b919c55-e39d-405c-ab86-ed254c6f16cd · outbound

This paper cites Learning to compare: Relation network for few-shot learning,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Learning to compare: Relation network for few-shot learning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:59:53.115469Z

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Observation 4fc3d953-1005-4d52-89e1-833db068bac4 · outbound

This paper cites Open-World Visual Recognition Using Knowledge Graphs.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Open-World Visual Recognition Using Knowledge Graphs

Reference 52

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Observation d47269de-5a14-490d-87bb-7ed4439a295b · outbound

This paper cites Inference with the universum,.

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning Inference with the universum,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:59:53.100526Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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