[PDF][PDF] Deep Learning Methods for Calibrated Photometric Stereo and Beyond
Photometric stereo recovers the surface normals of an object from multiple images with
varying shading cues, ie, modeling the relationship between surface orientation and …
varying shading cues, ie, modeling the relationship between surface orientation and …
Deep Learning Methods for Calibrated Photometric Stereo and Beyond
Photometric stereo recovers the surface normals of an object from multiple images with
varying shading cues, ie, modeling the relationship between surface orientation and …
varying shading cues, ie, modeling the relationship between surface orientation and …
En-compactness: Self-distillation embedding & contrastive generation for generalized zero-shot learning
Generalized zero-shot learning (GZSL) requires a classifier trained on seen classes that can
recognize objects from both seen and unseen classes. Due to the absence of unseen …
recognize objects from both seen and unseen classes. Due to the absence of unseen …
Normattention-psn: A high-frequency region enhanced photometric stereo network with normalized attention
Photometric stereo aims to recover the surface normals of a 3D object from various shading
cues, establishing the relationship between two-dimensional images and the object …
cues, establishing the relationship between two-dimensional images and the object …
A critical analysis of nerf-based 3d reconstruction
This paper presents a critical analysis of image-based 3D reconstruction using neural
radiance fields (NeRFs), with a focus on quantitative comparisons with respect to traditional …
radiance fields (NeRFs), with a focus on quantitative comparisons with respect to traditional …
Estimating high-resolution surface normals via low-resolution photometric stereo images
Acquiring high-resolution 3D surface structures is a crucial task in computer vision as it
provides more detailed surface textures and clearer structures. Photometric stereo can …
provides more detailed surface textures and clearer structures. Photometric stereo can …
Generalized zero-shot learning via disentangled representation
Abstract Zero-Shot Learning (ZSL) aims to recognize images belonging to unseen classes
that are unavailable in the training process, while Generalized Zero-Shot Learning (GZSL) is …
that are unavailable in the training process, while Generalized Zero-Shot Learning (GZSL) is …
GR-PSN: Learning to estimate surface normal and reconstruct photometric stereo images
In this paper, we propose a novel method, namely GR-PSN, which learns surface normals
from photometric stereo images and generates the photometric images under distant …
from photometric stereo images and generates the photometric images under distant …
Recovering surface normal and arbitrary images: A dual regression network for photometric stereo
Photometric stereo recovers three-dimensional (3D) object surface normal from multiple
images under different illumination directions. Traditional photometric stereo methods suffer …
images under different illumination directions. Traditional photometric stereo methods suffer …
Diligent-pi: Photometric stereo for planar surfaces with rich details-benchmark dataset and beyond
Photometric stereo aims to recover detailed surface shapes from images captured under
varying illuminations. However, existing real-world datasets primarily focus on evaluating …
varying illuminations. However, existing real-world datasets primarily focus on evaluating …