13 citations · 17 across the 5 of their papers we have counts for
5 papers
Double Descent of Discrepancy: A Task-, Data-, and Model-Agnostic Phenomenon
Yifan Luo, Bin Dong
In this paper, we studied two identically-trained neural networks (i.e. networks with the same architecture, trained on the same dataset using the same algorithm, but with differen…
Unsupervised Image Denoising with Score Function
Yutong Xie, Mingze Yuan, Bin Dong +1
Though achieving excellent performance in some cases, current unsupervised learning methods for single image denoising usually have constraints in applications. In this paper, we p…
Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization
Mingze Yuan, Yingda Xia, Hexin Dong +13
Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically signi…
Diffusion Model for Generative Image Denoising
Yutong Xie, Minne Yuan, Bin Dong +1
In supervised learning for image denoising, usually the paired clean images and noisy images are collected or synthesised to train a denoising model. L2 norm loss or other distance…
Implicit Feature Refinement for Instance Segmentation
Lufan Ma, Tiancai Wang, Bin Dong +3
We propose a novel implicit feature refinement module for high-quality instance segmentation. Existing image/video instance segmentation methods rely on explicitly stacked convolut…