5 papers
Cepheid: Decoupling Scale from Structure for Cross-Family Motion Completion
Chih-Hai Su, Tsung-Wei Ke, Yu-Lun Liu
Sparse-to-dense motion completion recovers dense mesh motion from sparse vertex displacements. Residual priors trained on one geometry family frequently fail to beat parameter-free…
LightsOut: Diffusion-based Outpainting for Enhanced Lens Flare Removal
Shr-Ruei Tsai, Wei-Cheng Chang, Jie-Ying Lee +2
Lens flare significantly degrades image quality, impacting critical computer vision tasks like object detection and autonomous driving. Recent Single Image Flare Removal (SIFR) met…
See, Point, Fly: A Learning-Free VLM Framework for Universal Unmanned Aerial Navigation
Chih Yao Hu, Yang-Sen Lin, Yuna Lee +7
We present See, Point, Fly (SPF), a training-free aerial vision-and-language navigation (AVLN) framework built atop vision-language models (VLMs). SPF is capable of navigating to a…
BoostMVSNeRFs: Boosting MVS-based NeRFs to Generalizable View Synthesis in Large-scale Scenes
Chih-Hai Su, Chih-Yao Hu, Shr-Ruei Tsai +3
While Neural Radiance Fields (NeRFs) have demonstrated exceptional quality, their protracted training duration remains a limitation. Generalizable and MVS-based NeRFs, although cap…
DeNVeR: Deformable Neural Vessel Representations for Unsupervised Video Vessel Segmentation
Chun-Hung Wu, Shih-Hong Chen, Chih-Yao Hu +6
This paper presents Deformable Neural Vessel Representations (DeNVeR), an unsupervised approach for vessel segmentation in X-ray angiography videos without annotated ground truth.…