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07/17/2023
Dense Affinity Matching for Few-Shot Segmentation
Few-Shot Segmentation (FSS) aims to segment the novel class images with ...
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06/06/2023
DenseDINO: Boosting Dense Self-Supervised Learning with Token-Based Point-Level Consistency
In this paper, we propose a simple yet effective transformer framework f...
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06/06/2023
MetaGait: Learning to Learn an Omni Sample Adaptive Representation for Gait Recognition
Gait recognition, which aims at identifying individuals by their walking...
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06/06/2023
GaitGCI: Generative Counterfactual Intervention for Gait Recognition
Gait is one of the most promising biometrics that aims to identify pedes...
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03/11/2023
Multi-Context Interaction Network for Few-Shot Segmentation
Few-Shot Segmentation (FSS) is challenging for limited support images an...
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09/08/2019
Meta-Transfer Networks for Zero-Shot Learning
Zero-Shot Learning (ZSL) aims at recognizing unseen categories using som...
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08/26/2019
A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification
Zero-Shot Classification (ZSC) equips the learned model with the ability...
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11/20/2018
Bi-Adversarial Auto-Encoder for Zero-Shot Learning
Existing generative Zero-Shot Learning (ZSL) methods only consider the u...
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05/21/2018
Stacked Semantic-Guided Attention Model for Fine-Grained Zero-Shot Learning
Zero-Shot Learning (ZSL) is achieved via aligning the semantic relations...
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02/06/2018
Attribute-Guided Network for Cross-Modal Zero-Shot Hashing
Zero-Shot Hashing aims at learning a hashing model that is trained only ...
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12/26/2017
Zero-Shot Learning via Latent Space Encoding
Zero-Shot Learning (ZSL) is typically achieved by resorting to a class s...
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03/27/2017
Transductive Zero-Shot Learning with Adaptive Structural Embedding
Zero-shot learning (ZSL) endows the computer vision system with the infe...
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03/27/2017
