80 citations · 137 across the 33 of their papers we have counts for
9 papers · 1 filter
Name Your Colour For the Task: Artificially Discover Colour Naming via Colour Quantisation Transformer
Shenghan Su, Lin Gu, Yue Yang +2
The long-standing theory that a colour-naming system evolves under dual pressure of efficient communication and perceptual mechanism is supported by more and more linguistic studie…
Improving Fairness in Image Classification via Sketching
Ruichen Yao, Ziteng Cui, Xiaoxiao Li +1
Fairness is a fundamental requirement for trustworthy and human-centered Artificial Intelligence (AI) system. However, deep neural networks (DNNs) tend to make unfair predictions w…
Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection
Ziteng Cui, Yingying Zhu, Lin Gu +5
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images. Most of these algorithms assume the…
Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection
Ziteng Cui, Guo-Jun Qi, Lin Gu +3
Dark environment becomes a challenge for computer vision algorithms owing to insufficient photons and undesirable noise. To enhance object detection in a dark environment, we propo…
You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction
Ziteng Cui, Kunchang Li, Lin Gu +5
Challenging illumination conditions (low-light, under-exposure and over-exposure) in the real world not only cast an unpleasant visual appearance but also taint the computer vision…
Explainable Analysis of Deep Learning Methods for SAR Image Classification
Shenghan Su, Ziteng Cui, Weiwei Guo +2
Deep learning methods exhibit outstanding performance in synthetic aperture radar (SAR) image interpretation tasks. However, these are black box models that limit the comprehension…
MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
Renrui Zhang, Han Qiu, Tai Wang +7
Monocular 3D object detection has long been a challenging task in autonomous driving. Most existing methods follow conventional 2D detectors to first localize object centers, and t…
Linear Array Network for Low-light Image Enhancement
Keqi Wang, Ziteng Cui, Jieru Jia +6
Convolution neural networks (CNNs) based methods have dominated the low-light image enhancement tasks due to their outstanding performance. However, the convolution operation is ba…
RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images
Ziteng Cui, Yingying Zhu, Lin Gu +5
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images. However, most of these algorithms assum…