7 citations · 9 across the 4 of their papers we have counts for
5 papers
Denoising-GS: Gaussian Splatting with Spatial-aware Denoising
Qingyuan Zhou, Xinyi Liu, Weidong Yang +5
Recent advances in 3D Gaussian Splatting (3DGS) have achieved remarkable success in high-fidelity Novel View Synthesis (NVS), yet the optimization process inevitably introduces noi…
Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation
Ning-Hsu Wang, Yu-Lun Liu
Accurately estimating depth in 360-degree imagery is crucial for virtual reality, autonomous navigation, and immersive media applications. Existing depth estimation methods designe…
Bridging Unsupervised and Supervised Depth from Focus via All-in-Focus Supervision
Ning-Hsu Wang, Ren Wang, Yu-Lun Liu +4
Depth estimation is a long-lasting yet important task in computer vision. Most of the previous works try to estimate depth from input images and assume images are all-in-focus (AiF…
Indoor Panorama Planar 3D Reconstruction via Divide and Conquer
Cheng Sun, Chi-Wei Hsiao, Ning-Hsu Wang +2
Indoor panorama typically consists of human-made structures parallel or perpendicular to gravity. We leverage this phenomenon to approximate the scene in a 360-degree image with (H…
360SD-Net: 360° Stereo Depth Estimation with Learnable Cost Volume
Ning-Hsu Wang, Bolivar Solarte, Yi-Hsuan Tsai +2
Recently, end-to-end trainable deep neural networks have significantly improved stereo depth estimation for perspective images. However, 360° images captured under equirectangular…