most citedLight Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions

44 citations · 94 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202431 cited

NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods

Qiang Qu, Hanxue Liang, Xiaoming Chen +2

Neural View Synthesis (NVS) has demonstrated efficacy in generating high-fidelity dense viewpoint videos using a image set with sparse views. However, existing quality assessment m…

cs.CV202416 cited

EvRepSL: Event-Stream Representation via Self-Supervised Learning for Event-Based Vision

Qiang Qu, Xiaoming Chen, Yuk Ying Chung +1

Event-stream representation is the first step for many computer vision tasks using event cameras. It converts the asynchronous event-streams into a formatted structure so that conv…

eess.IV202444 cited

Light Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions

Qiang Qu, Xiaoming Chen, Vera Chung +1

In multimedia broadcasting, no-reference image quality assessment (NR-IQA) is used to indicate the user-perceived quality of experience (QoE) and to support intelligent data transm…

cs.CV20243 cited

Beyond Gaussians: Fast and High-Fidelity 3D Splatting with Linear Kernels

Haodong Chen, Runnan Chen, Qiang Qu +4

Recent advancements in 3D Gaussian Splatting (3DGS) have substantially improved novel view synthesis, enabling high-quality reconstruction and real-time rendering. However, blurrin…

cs.CV2024

Adaptively Augmented Consistency Learning: A Semi-supervised Segmentation Framework for Remote Sensing

Hui Ye, Haodong Chen, Xiaoming Chen +1

Remote sensing (RS) involves the acquisition of data about objects or areas from a distance, primarily to monitor environmental changes, manage resources, and support planning and…