Name
Abstract | ||
|---|---|---|
A common practice to account for psychophysical biases in vision is to frame them as consequences of a dynamic process relying on optimal inference with respect to a generative model. The study presented here details the complete formulation of such a generative model intended to probe visual motion perception with a dynamic texture model. It is derived in a set of axiomatic steps constrained by b... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1162/neco_a_01142 | Neural Computation |
DocType | Volume | Issue |
Journal | 30 | 12 |
ISSN | Citations | PageRank |
0899-7667 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonathan Vacher | 1 | 4 | 2.16 |
| Andrew Meso | 2 | 4 | 1.73 |
| Laurent U. Perrinet | 3 | 130 | 13.99 |
| Gabriel Peyré | 4 | 1195 | 79.60 |