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Weakly-Supervised Object Localization

Weakly supervised object localization (WSOL) learns to localize objects with only image-level labels, no object level labels (bonding boxes, etc.,) is needed. It is more attractive since image-level labels are much easier and cheaper to obtain.

Papers

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Showing 51–75 of 140 papers

TitleStatusHype
CaFT: Clustering and Filter on Tokens of Transformer for Weakly Supervised Object Localization—0
Category-aware Allocation Transformer for Weakly Supervised Object Localization—0
Compression and Localization in Reinforcement Learning for ATARI Games—0
Constrained Sampling for Class-Agnostic Weakly Supervised Object Localization—0
Deep Self-Taught Learning for Weakly Supervised Object Localization—0
Density-Based Region Search with Arbitrary Shape for Object Localization—0
Discriminative Sampling of Proposals in Self-Supervised Transformers for Weakly Supervised Object Localization—0
Diverse Instance Discovery: Vision-Transformer for Instance-Aware Multi-Label Image Recognition—0
Dual-attention Focused Module for Weakly Supervised Object Localization—0
Entropy Guided Adversarial Model for Weakly Supervised Object Localization—0
Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization—0
Weakly-supervised Object Localization for Few-shot Learning and Fine-grained Few-shot Learning—0
Fine-Grained Attention for Weakly Supervised Object Localization—0
Foreground Activation Maps for Weakly Supervised Object Localization—0
Hierarchical Complementary Learning for Weakly Supervised Object Localization—0
How hard can it be? Estimating the difficulty of visual search in an image—0
Improved Techniques For Weakly-Supervised Object Localization—0
Improving Few-shot Learning with Weakly-supervised Object Localization—0
Improving Weakly-Supervised Object Localization By Micro-Annotation—0
Improving Weakly-Supervised Object Localization Using Adversarial Erasing and Pseudo Label—0
Information Entropy Based Feature Pooling for Convolutional Neural Networks—0
Categorical Knowledge Fused Recognition: Fusing Hierarchical Knowledge with Image Classification through Aligning and Deep Metric Learning—0
LCTR: On Awakening the Local Continuity of Transformer for Weakly Supervised Object Localization—0
Learning Consistency from High-quality Pseudo-labels for Weakly Supervised Object Localization—0
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection—0
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