227 citations · 551 across the 25 of their papers we have counts for
5 papers · 1 filter
GlowGAN: Unsupervised Learning of HDR Images from LDR Images in the Wild
Chao Wang, Ana Serrano, Xingang Pan +5
Most in-the-wild images are stored in Low Dynamic Range (LDR) form, serving as a partial observation of the High Dynamic Range (HDR) visual world. Despite limited dynamic range, th…
gCoRF: Generative Compositional Radiance Fields
Mallikarjun BR, Ayush Tewari, Xingang Pan +2
3D generative models of objects enable photorealistic image synthesis with 3D control. Existing methods model the scene as a global scene representation, ignoring the compositional…
Voxurf: Voxel-based Efficient and Accurate Neural Surface Reconstruction
Tong Wu, Jiaqi Wang, Xingang Pan +4
Neural surface reconstruction aims to reconstruct accurate 3D surfaces based on multi-view images. Previous methods based on neural volume rendering mostly train a fully implicit m…
GAN2X: Non-Lambertian Inverse Rendering of Image GANs
Xingang Pan, Ayush Tewari, Lingjie Liu +1
2D images are observations of the 3D physical world depicted with the geometry, material, and illumination components. Recovering these underlying intrinsic components from 2D imag…
Disentangled3D: Learning a 3D Generative Model with Disentangled Geometry and Appearance from Monocular Images
Ayush Tewari, Mallikarjun B R, Xingang Pan +3
Learning 3D generative models from a dataset of monocular images enables self-supervised 3D reasoning and controllable synthesis. State-of-the-art 3D generative models are GANs whi…