most citedYou Only Train Once: Learning a General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection

59 citations · 71 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023★ 4 cited

The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation

Lingdong Kong, Yaru Niu, Shaoyuan Xie +39

Accurate depth estimation under out-of-distribution (OoD) scenarios, such as adverse weather conditions, sensor failure, and noise contamination, is desirable for safety-critical a…

eess.IV2023★ 59 cited

You Only Train Once: Learning a General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection

Zhaoxu Li, Yingqian Wang, Chao Xiao +3

In this paper, we introduce a new approach to address the challenge of generalization in hyperspectral anomaly detection (AD). Our method eliminates the need for adjusting paramete…

cs.CV2022★ 4 cited

Ranking-Based Siamese Visual Tracking

Feng Tang, Qiang Ling

Current Siamese-based trackers mainly formulate the visual tracking into two independent subtasks, including classification and localization. They learn the classification subnetwo…

cs.CV2022★ 4 cited

Multi-model Ensemble Learning Method for Human Expression Recognition

Jun Yu, Zhongpeng Cai, Peng He +2

Analysis of human affect plays a vital role in human-computer interaction (HCI) systems. Due to the difficulty in capturing large amounts of real-life data, most of the current met…

cs.CY2022

Cognitive Diagnosis with Explicit Student Vector Estimation and Unsupervised Question Matrix Learning

Lu Dong, Zhenhua Ling, Qiang Ling +1

Cognitive diagnosis is an essential task in many educational applications. Many solutions have been designed in the literature. The deterministic input, noisy "and" gate (DINA) mod…