activity
20242026
collaborators

10 papers

cs.SD2026

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…

cs.CV2026

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…

cs.SD2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…