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Found 5 papers, 1 papers with code
Weakly-Supervised 3D Scene Graph Generation via Visual-Linguistic Assisted Pseudo-labeling
However, previous 3D scene graph generation methods utilize a fully supervised learning manner and require a large amount of entity-level annotation data of objects and relations, which is extremely resource-consuming and tedious to obtain.
Compositional Oil Spill Detection Based on Object Detector and Adapted Segment Anything Model from SAR Images
The adapted SAM, combining a frozen SAM with a learnable Adapter module, can enhance SAM's ability to segment ambiguous objects.
Weakly-Supervised 3D Visual Grounding based on Visual Linguistic Alignment
During the inference stage, the learned text-3D correspondence will help us ground the text queries to the 3D target objects even without 2D images.
URetinex-Net: Retinex-Based Deep Unfolding Network for Low-Light Image Enhancement
Retinex model-based methods have shown to be effective in layer-wise manipulation with well-designed priors for low-light image enhancement.
Superpixel Segmentation Based on Spatially Constrained Subspace Clustering
Consequently, we devise a spatial regularization and propose a novel convex locality-constrained subspace clustering model that is able to constrain the spatial adjacent pixels with similar attributes to be clustered into a superpixel and generate the content-aware superpixels with more detailed boundaries.
