Results 211 to 220 of about 2,853,899 (260)
IA-3DGS Identity-Anchored Dynamic Gaussian Splatting for Long-Term Facial Detail Preservation. [PDF]
Sensors (Basel)Zhao Z, Yin L, Wang S, Gao J.
europepmc +1 more source
A solution to generalized learning from small training sets found in infants' repeated visual experiences of individual objects. [PDF]
Proc Natl Acad Sci U S ARamirez FM +3 more
europepmc +1 more source
Color constancy mechanisms in virtual reality environments. [PDF]
J VisGil RodrÃguez R +5 more
europepmc +1 more source
Complex dark environment-oriented object detection method based on YOLO-AS. [PDF]
Sci RepRen B, Xu Z, Zhao J, Hao R, Zhang J.
europepmc +1 more source
Computational Color Constancy: Survey and Experiments
IEEE Transactions on Image Processing, 2011 Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the-art methods. Several criteria are proposed that are used to assess the approaches.
Joost van de Weijer +2 more
exaly +5 more sources
Computational Color Constancy Using Chromagenic Filters in Color Filter Arrays [PDF]
Proceedings of SPIE, 2012 This is the copy of journal's version originally published in Proc. SPIE 8298: http://dx.doi.org/10.1117/12.912073. Reprinted with permission of SPIE.
Raju Shrestha, Jon Yngve Hardeberg
exaly +6 more sources
Sensor Sharpening for Computational Color Constancy [PDF]
Journal of the Optical Society of America A: Optics and Image Science, and Vision, 2001 Sensor sharpening [J. Opt. Soc. Am. A 11, 1553 (1994)] has been proposed as a method for improving computational color constancy, but it has not been thoroughly tested in practice with existing color constancy algorithms. In this paper we study sensor sharpening in the context of viable color constancy processing, both theoretically and empirically ...
Kobus Barnard, Funt, Brian
exaly +3 more sources