Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Xi-Sheng Fang

dblp:99/5434 · DBLP profile ↗
← Back
3ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3Graphics, computer vision, multimedia, augmented reality and games · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
3 papers
Image and video processing · 50% Geometric modeling and processing · 30% Computational photography and imaging · 20%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image restoration
reflection removal
0.021997
Separation of Reflection Components Using Color and Polarization · Int. J. Comput. Vis. 1997
Removal of specularities using color and polarization · CVPR 1993
Geometric modeling and processing
deformable models
0.011994
The extruded generalized cylinder: a deformable model for object recovery · CVPR 1994
Geometric modeling and processing › shape representation › primitive-based representation
generalized cylinders
0.011994
The extruded generalized cylinder: a deformable model for object recovery · CVPR 1994
Computational photography and imaging
polarization imaging
0.011993
Removal of specularities using color and polarization · CVPR 1993
Image and video processing › image restoration › reflection removal
specular-diffuse separation
0.011993
Removal of specularities using color and polarization · CVPR 1993
Computational photography and imaging
photometric analysis
0.011997
Separation of Reflection Components Using Color and Polarization · Int. J. Comput. Vis. 1997
Medical and health informatics › medical imaging
medical image analysis
0.011994
The extruded generalized cylinder: a deformable model for object recovery · CVPR 1994

Methods — techniques the papers use, named apart from their topics

color analysis · 0.0physically-motivated deformation · 0.0polarization · 0.0polarization analysis · 0.0
YearPublicationVenuePosition
1997 Separation of Reflection Components Using Color and Polarization
Shree K. Nayar, Xi-Sheng Fang, Terrance E. Boult
Int. J. Comput. Vis.2
1994 The extruded generalized cylinder: a deformable model for object recovery
abstract
There is increasing interest in the recovery of generalized cylinders (GCs) with curved spines. However, existing formulations of such GCs, for example those based an the Frenet-Serret frame or the tube model, suffer serious drawbacks: discontinuities, a lack of expressive power, "narrowing" in the plane normal to the spine, non-intuitive twisting behavior, and/or off-axis nonorthogonality of their local coordinate systems. We discuss some of the problems associated with the non-orthogonality of the coordinate system based on the Frenet-Serret frame. This non-orthogonality is induced by torsion effects and we show how to correct for it. We then introduce a new model, the extruded GC (EGC) model, which overcomes all the problems mentioned above. For complex axes, the EGC model is also simpler to understand and use than existing models. The EGC model is further extended by including local surface deformations. Recovery of the deformable EGC via a physically-motivated paradigm is demonstrated on pre-segmented data from a human carotid artery.>
Thomas O'Donnell, Terrance E. Boult, Xi-Sheng Fang, Alok Gupta
CVPR3
1993 Removal of specularities using color and polarization
abstract
An algorithm for separating the specular and diffuse components of reflection from images is presented. The method uses color and polarization simultaneously to obtain strong constraints on the reflection components at each image point. Polarization is used to locally determine the color of the specular component, constraining the diffuse color at a pixel to a one-dimensional linear subspace. This subspace is used to find neighboring pixels whose color is consistent with the pixel. Diffuse color information from consistent neighbors is used to determine the diffuse color of the pixel. In contrast to previous separation algorithms, the proposed method can handle highlights that have a varying diffuse component, as well as highlights that include regions with different reflectance and material properties. Experimental results obtained by applying the algorithm to complex scenes with textured objects and strong interreflections are presented.>
Shree K. Nayar, Xi-Sheng Fang, Terrance E. Boult
CVPR2