44 citations · 136 across the 14 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
Can Large Language Models Grasp Event Signals? Exploring Pure Zero-Shot Event-based Recognition
Zongyou Yu, Qiang Qu, Xiaoming Chen +1
Recent advancements in event-based zero-shot object recognition have demonstrated promising results. However, these methods heavily depend on extensive training and are inherently…
E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning
Qiang Qu, Yiran Shen, Xiaoming Chen +2
The bio-inspired event cameras or dynamic vision sensors are capable of asynchronously capturing per-pixel brightness changes (called event-streams) in high temporal resolution and…