44 citations · 136 across the 14 of their papers we have counts for
14 papers
DynFOA: Generating First-Order Ambisonics with Conditional Diffusion for Dynamic and Acoustically Complex 360-Degree Videos
Ziyu Luo, Lin Chen, Qiang Qu +2
Spatial audio is crucial for immersive 360-degree video experiences, yet most 360-degree videos lack it due to the difficulty of capturing spatial audio during recording. Automatic…
DynFOA: Generating First-Order Ambisonics with Conditional Diffusion for Dynamic and Acoustically Complex 360-Degree Videos
Ziyu Luo, Lin Chen, Qiang Qu +2
Spatial audio is crucial for immersive 360-degree video experiences, yet most 360-degree videos lack it due to the difficulty of capturing spatial audio during recording. Automatic…
AccidentSim: Generating Vehicle Collision Videos with Physically Realistic Collision Trajectories from Real-World Accident Reports
Xiangwen Zhang, Qian Zhang, Longfei Han +3
Collecting real-world vehicle accident videos for autonomous driving research is challenging due to their rarity and complexity. While existing driving video generation methods may…
EvAnimate: Event-conditioned Image-to-Video Generation for Human Animation
Qiang Qu, Ming Li, Xiaoming Chen +1
Conditional human animation traditionally animates static reference images using pose-based motion cues extracted from video data. However, these video-derived cues often suffer fr…
LLM-EvRep: Learning an LLM-Compatible Event Representation Using a Self-Supervised Framework
Zongyou Yu, Qiang Qu, Qian Zhang +2
Recent advancements in event-based recognition have demonstrated significant promise, yet most existing approaches rely on extensive training, limiting their adaptability for effic…
NVS-SQA: Exploring Self-Supervised Quality Representation Learning for Neurally Synthesized Scenes without References
Qiang Qu, Yiran Shen, Xiaoming Chen +3
Neural View Synthesis (NVS), such as NeRF and 3D Gaussian Splatting, effectively creates photorealistic scenes from sparse viewpoints, typically evaluated by quality assessment met…
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…
LFACon: Introducing Anglewise Attention to No-Reference Quality Assessment in Light Field Space
Qiang Qu, Xiaoming Chen, Yuk Ying Chung +1
Light field imaging can capture both the intensity information and the direction information of light rays. It naturally enables a six-degrees-of-freedom viewing experience and dee…
Towards Understanding Chinese Checkers with Heuristics, Monte Carlo Tree Search, and Deep Reinforcement Learning
Ziyu Liu, Meng Zhou, Weiqing Cao +3
The game of Chinese Checkers is a challenging traditional board game of perfect information that differs from other traditional games in two main aspects: first, unlike Chess, all…