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Found 4 papers, 3 papers with code
Beyond Literal Descriptions: Understanding and Locating Open-World Objects Aligned with Human Intentions
Previous datasets and methods for classic VG task mainly rely on the prior assumption that the given expression must literally refer to the target object, which greatly impedes the practical deployment of agents in real-world scenarios.
Adaptive FSS: A Novel Few-Shot Segmentation Framework via Prototype Enhancement
In this paper, we propose a novel framework based on the adapter mechanism, namely Adaptive FSS, which can efficiently adapt the existing FSS model to the novel classes.
Unveiling Parts Beyond Objects:Towards Finer-Granularity Referring Expression Segmentation
To foster future research into fine-grained visual grounding, our benchmark RefCOCOm, the MRES-32M dataset and model UniRES will be publicly available at https://github. com/Rubics-Xuan/MRES
CM-MaskSD: Cross-Modality Masked Self-Distillation for Referring Image Segmentation
Referring image segmentation (RIS) is a fundamental vision-language task that intends to segment a desired object from an image based on a given natural language expression.
