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Found 6 papers, 6 papers with code
Rˆ3Net:Relation-embedded Representation Reconstruction Network for Change Captioning
In this paper, we propose a Relation-embedded Representation Reconstruction Network (Rˆ3Net) to explicitly distinguish the real change from the large amount of clutter and irrelevant changes.
Self-supervised Cross-view Representation Reconstruction for Change Captioning
Change captioning aims to describe the difference between a pair of similar images.
Neighborhood Contrastive Transformer for Change Captioning
Change captioning is to describe the semantic change between a pair of similar images in natural language.
LS-GAN: Iterative Language-based Image Manipulation via Long and Short Term Consistency Reasoning
To address this issue, we propose a novel Long and Short term consistency reasoning Generative Adversarial Network (LS-GAN), which enhances the awareness of previous objects with current instruction and better maintains the consistency with the user's intent under the continuous iterations.
R$^3$Net:Relation-embedded Representation Reconstruction Network for Change Captioning
In this paper, we propose a Relation-embedded Representation Reconstruction Network (R$^3$Net) to explicitly distinguish the real change from the large amount of clutter and irrelevant changes.
