On the Functional Role of Implicit Visual Memory for the Adaptive Deployment of Attention Across Scenes

By Marvin M. Chun, Ken Nakayama. 2000

207 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/19eb1b71b9f0a6a566b4dbce15257fb2e0602ee3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. A. Hollingworth
2. Mary M. Hayhoe
3. J. Henderson
4. Richard N. Aslin
5. József Fiser
6. J. Pelz
7. Tim J. Smith
8. B. Tatler

In Computer Vision and Pattern Recognition

1. Mary M. Hayhoe
2. A. Hollingworth
3. J. Henderson
4. J. Pelz
5. Tim J. Smith
6. Keith Rayner
7. Antonio Torralba
8. B. Tatler

Citations in the corpus

• Accurate visual memory for previously attended objects in natural scenes (2002, background): “It therefore appears that LTM plays an important role in online scene perception (see also Chun & Nakayama, 2000).”
• Visual memory and motor planning in a natural task. (2003, background): “It also seems likely that fixating the location of a future target facilitates the programing of the saccade, and perhaps initiates programming the reach (McPeek & Nakayama, 1999; Chun & Nakayama, 2000; Zelinsky et al, 1997).”
• Statistical learning of higher-order temporal structure from visual shape sequences. (2002, background): “…that context (e.g., preceding scenes in the sequential presentation of many scenes) implicitly promotes associations across scenes (Chun & Jiang, 1998, 1999; Chun & Nakayama, 2000; Olson & Chun, 2001), and that target priming can facilitate visual search (Maljkovic & Nakayama, 1994, 1996, 2000).”