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Found 4 papers, 3 papers with code
Masked Image Residual Learning for Scaling Deeper Vision Transformers
With the same level of computational complexity as ViT-Base and ViT-Large, we instantiate 4. 5$\times$ and 2$\times$ deeper ViTs, dubbed ViT-S-54 and ViT-B-48.
Learning to Upsample by Learning to Sample
We present DySample, an ultra-lightweight and effective dynamic upsampler.
SAPA: Similarity-Aware Point Affiliation for Feature Upsampling
We introduce point affiliation into feature upsampling, a notion that describes the affiliation of each upsampled point to a semantic cluster formed by local decoder feature points with semantic similarity.
Ranked #5 on
Feature Upsampling
on ImageNet
FADE: Fusing the Assets of Decoder and Encoder for Task-Agnostic Upsampling
We consider the problem of task-agnostic feature upsampling in dense prediction where an upsampling operator is required to facilitate both region-sensitive tasks like semantic segmentation and detail-sensitive tasks such as image matting.
