24 citations · 24 across the 18 of their papers we have counts for
7 papers · 1 filter
Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation
Yuheng Shi, Minjing Dong, Chang Xu
While Contrastive Language-Image Pre-training (CLIP) has advanced open-vocabulary predictions, its performance on semantic segmentation remains suboptimal. This shortfall primarily…
Feature Clipping for Uncertainty Calibration
Linwei Tao, Minjing Dong, Chang Xu
Deep neural networks (DNNs) have achieved significant success across various tasks, but ensuring reliable uncertainty estimates, known as model calibration, is crucial for their sa…
Consistency Calibration: Improving Uncertainty Calibration via Consistency among Perturbed Neighbors
Linwei Tao, Haolan Guo, Minjing Dong +1
Calibration is crucial in deep learning applications, especially in fields like healthcare and autonomous driving, where accurate confidence estimates are vital for decision-making…
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
Jinxu Lin, Linwei Tao, Minjing Dong +1
As diffusion models become increasingly popular, the misuse of copyrighted and private images has emerged as a major concern. One promising solution to mitigate this issue is ident…
VSSD: Vision Mamba with Non-Causal State Space Duality
Yuheng Shi, Minjing Dong, Mingjia Li +1
Vision transformers have significantly advanced the field of computer vision, offering robust modeling capabilities and global receptive field. However, their high computational de…
Efficient Image-to-Image Diffusion Classifier for Adversarial Robustness
Hefei Mei, Minjing Dong, Chang Xu
Diffusion models (DMs) have demonstrated great potential in the field of adversarial robustness, where DM-based defense methods can achieve superior defense capability without adve…
Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model
Yuheng Shi, Minjing Dong, Chang Xu
Despite the significant achievements of Vision Transformers (ViTs) in various vision tasks, they are constrained by the quadratic complexity. Recently, State Space Models (SSMs) ha…