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Found 3 papers, 2 papers with code
CEDNet: A Cascade Encoder-Decoder Network for Dense Prediction
A hallmark of CEDNet is its ability to incorporate high-level features from early stages to guide low-level feature learning in subsequent stages, thereby enhancing the effectiveness of multi-scale feature fusion.
Open-vocabulary Object Segmentation with Diffusion Models
The goal of this paper is to extract the visual-language correspondence from a pre-trained text-to-image diffusion model, in the form of segmentation map, i. e., simultaneously generating images and segmentation masks for the corresponding visual entities described in the text prompt.
A Simple Plugin for Transforming Images to Arbitrary Scales
Existing models on super-resolution often specialized for one scale, fundamentally limiting their use in practical scenarios.
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