output
20202026
most citedA Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Samples

373 citations

Showing cs.CVShow all

11 papers · 1 filter

cs.CV2025

DreamLifting: A Plug-in Module Lifting MV Diffusion Models for 3D Asset Generation

Ze-Xin Yin, Jiaxiong Qiu, Liu Liu +5

The labor- and experience-intensive creation of 3D assets with physically based rendering (PBR) materials demands an autonomous 3D asset creation pipeline. However, most existing 3…

cs.CV2024★ 20 cited

Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning

Hongze Zhu, Guoyang Xie, Chengbin Hou +4

High-resolution point clouds~(HRPCD) anomaly detection~(AD) plays a critical role in precision machining and high-end equipment manufacturing. Despite considerable 3D-AD methods th…

cs.CV2023★ 77 cited

Precise Facial Landmark Detection by Reference Heatmap Transformer

Jun Wan, Jun Liu, Jie Zhou +5

Most facial landmark detection methods predict landmarks by mapping the input facial appearance features to landmark heatmaps and have achieved promising results. However, when the…

cs.CV2022★ 1 cited

Improving Image Clustering through Sample Ranking and Its Application to remote--sensing images

Qinglin Li, Guoping Qiu

Image clustering is a very useful technique that is widely applied to various areas, including remote sensing. Recently, visual representations by self-supervised learning have gre…

cs.CV2022★ 1 cited

Fusing Multiscale Texture and Residual Descriptors for Multilevel 2D Barcode Rebroadcasting Detection

Anselmo Ferreira, Changcheng Chen, Mauro Barni

Nowadays, 2D barcodes have been widely used for advertisement, mobile payment, and product authentication. However, in applications related to product authentication, an authentic…

cs.CV2022★ 72 cited

HIPA: Hierarchical Patch Transformer for Single Image Super Resolution

Qing Cai, Yiming Qian, Jinxing Li +4

Transformer-based architectures start to emerge in single image super resolution (SISR) and have achieved promising performance. Most existing Vision Transformers divide images int…