38 citations · 105 across the 8 of their papers we have counts for
8 papers
Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields
Wenbo Hu, Yuling Wang, Lin Ma +4
Despite the tremendous progress in neural radiance fields (NeRF), we still face a dilemma of the trade-off between quality and efficiency, e.g., MipNeRF presents fine-detailed and…
Scale-arbitrary Invertible Image Downscaling
Jinbo Xing, Wenbo Hu, Tien-Tsin Wong
Conventional social media platforms usually downscale the HR images to restrict their resolution to a specific size for saving transmission/storage cost, which leads to the super-r…
Conditional Directed Graph Convolution for 3D Human Pose Estimation
Wenbo Hu, Changgong Zhang, Fangneng Zhan +2
Graph convolutional networks have significantly improved 3D human pose estimation by representing the human skeleton as an undirected graph. However, this representation fails to r…
Sparse Needlets for Lighting Estimation with Spherical Transport Loss
Fangneng Zhan, Changgong Zhang, Wenbo Hu +4
Accurate lighting estimation is challenging yet critical to many computer vision and computer graphics tasks such as high-dynamic-range (HDR) relighting. Existing approaches model…
Bidirectional Projection Network for Cross Dimension Scene Understanding
Wenbo Hu, Hengshuang Zhao, Li Jiang +2
2D image representations are in regular grids and can be processed efficiently, whereas 3D point clouds are unordered and scattered in 3D space. The information inside these two vi…
GMLight: Lighting Estimation via Geometric Distribution Approximation
Fangneng Zhan, Yingchen Yu, Changgong Zhang +6
Inferring the scene illumination from a single image is an essential yet challenging task in computer vision and computer graphics. Existing works estimate lighting by regressing r…
Mononizing Binocular Videos
Wenbo Hu, Menghan Xia, Chi-Wing Fu +1
This paper presents the idea ofmono-nizingbinocular videos and a frame-work to effectively realize it. Mono-nize means we purposely convert abinocular video into a regular monocula…
DEMC: A Deep Dual-Encoder Network for Denoising Monte Carlo Rendering
Xin Yang, Wenbo Hu, Dawei Wang +5
In this paper, we present DEMC, a deep Dual-Encoder network to remove Monte Carlo noise efficiently while preserving details. Denoising Monte Carlo rendering is different from natu…