activity
20192023
most citedYou Only Need Adversarial Supervision for Semantic Image Synthesis

70 citations · 154 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2023

Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization

Yumeng Li, Dan Zhang, Margret Keuper +1

The generalization with respect to domain shifts, as they frequently appear in applications such as autonomous driving, is one of the remaining big challenges for deep learning mod…

cs.CV2023

High Dynamic Range Imaging with Context-aware Transformer

Fangfang Zhou, Dan Zhang, Zhenming Fu

Avoiding the introduction of ghosts when synthesising LDR images as high dynamic range (HDR) images is a challenging task. Convolutional neural networks (CNNs) are effective for HD…

cs.SD2023★ 1 cited

Learning From Yourself: A Self-Distillation Method for Fake Speech Detection

Jun Xue, Cunhang Fan, Jiangyan Yi +4

In this paper, we propose a novel self-distillation method for fake speech detection (FSD), which can significantly improve the performance of FSD without increasing the model comp…

cs.CV2022★ 5 cited

GOOD: Exploring Geometric Cues for Detecting Objects in an Open World

Haiwen Huang, Andreas Geiger, Dan Zhang

We address the task of open-world class-agnostic object detection, i.e., detecting every object in an image by learning from a limited number of base object classes. State-of-the-a…

cs.CV2022★ 3 cited

Intra-Source Style Augmentation for Improved Domain Generalization

Yumeng Li, Dan Zhang, Margret Keuper +1

The generalization with respect to domain shifts, as they frequently appear in applications such as autonomous driving, is one of the remaining big challenges for deep learning mod…

cs.CV2022★ 1 cited

One-Shot Synthesis of Images and Segmentation Masks

Vadim Sushko, Dan Zhang, Juergen Gall +1

Joint synthesis of images and segmentation masks with generative adversarial networks (GANs) is promising to reduce the effort needed for collecting image data with pixel-wise anno…