activity
20222024
most citedDreamDA: Generative Data Augmentation with Diffusion Models

3 citations · 4 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV20243 cited

DreamDA: Generative Data Augmentation with Diffusion Models

Yunxiang Fu, Chaoqi Chen, Yu Qiao +1

The acquisition of large-scale, high-quality data is a resource-intensive and time-consuming endeavor. Compared to conventional Data Augmentation (DA) techniques (e.g. cropping and…

cs.CV2024

Progressive Conservative Adaptation for Evolving Target Domains

Gangming Zhao, Chaoqi Chen, Wenhao He +5

Conventional domain adaptation typically transfers knowledge from a source domain to a stationary target domain. However, in many real-world cases, target data usually emerge seque…

cs.CV2023

Activate and Reject: Towards Safe Domain Generalization under Category Shift

Chaoqi Chen, Luyao Tang, Leitian Tao +4

Albeit the notable performance on in-domain test points, it is non-trivial for deep neural networks to attain satisfactory accuracy when deploying in the open world, where novel do…

cs.CV20231 cited

Unsupervised Adaptation of Polyp Segmentation Models via Coarse-to-Fine Self-Supervision

Jiexiang Wang, Chaoqi Chen

Unsupervised Domain Adaptation~(UDA) has attracted a surge of interest over the past decade but is difficult to be used in real-world applications. Considering the privacy-preserva…

cs.CV2022

Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis

Gangming Zhao, Quanlong Feng, Chaoqi Chen +2

During clinical practice, radiologists often use attributes, e.g. morphological and appearance characteristics of a lesion, to aid disease diagnosis. Effectively modeling attribute…