Scene Consistency in Object and Background Perception

By Jodi L. Davenport, Mary Potter. 2004

557 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Neuroscience, Cognitive Science & Psychology

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. Antonio Torralba
2. Aude Oliva
3. J. Henderson
4. Monica S. Castelhano
5. Moshe Bar
6. Abhinav Kumar Gupta
7. Li Fei-Fei
8. Abhinav Shrivastava

In Computer Vision and Pattern Recognition

1. Antonio Torralba
2. Li Fei-Fei
3. Luc Van Gool
4. Abhinav Kumar Gupta
5. Jitendra Malik
6. Trevor Darrell
7. Dacheng Tao
8. Andrew Zisserman

In Neuroscience

1. Antonio Torralba
2. J. Henderson
3. Aude Oliva
4. Moshe Bar
5. Mary Potter
6. Abhinav Kumar Gupta
7. Abhinav Shrivastava
8. Monica S. Castelhano

In Cognitive Science & Psychology

1. Antonio Torralba
2. J. Henderson
3. Aude Oliva
4. Moshe Bar
5. Mary Potter
6. Abhinav Kumar Gupta
7. Monica S. Castelhano
8. Li Fei-Fei

Citations in the corpus

• Conceptual Short Term Memory in Perception and Thought (2012, background): “Other studies with single pictures presented briefly and masked by a following stimulus have shown that objects in the foreground are more easily recognized if they are consistent with the background (and the background is more readily recognized if it is consistent with the foreground), showing tha”
• Visual objects in context (2004, background): “Two studies that tested this prediction found that an individually presented object was actually recognized more easily than the same object when it was embedded in a coherent scen”
• Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search. (2006, background): “…of objects, and task constraints have been shown to play a key role in modulating where attention and eye movement go (Chun & Jiang, 1998; Davenport & Potter, 2004; DeGraef, 1992; Henderson, 2003; Neider & Zelinski, 2006; Noton & Stark, 1971; Oliva, Torralba, Castelhano & Henderson,…”
• Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions (2009, background): “It is conceivable that the detection of typical objects (e.g., a car) helps with determining the scene category (e.g., highway), as has been shown in [17, 6 ]. On the other hand, it is also possible that information flows the other way, that scene-specific information in PPA and RSC feeds into LOC ”
• The natural/man-made distinction is made before basic-level distinctions in scene gist processing (2010, unknown): “…later cognitive processes, such as attention within scenes (Eckstein, Drescher, & Shimozaki, 2006; Gordon, 2004; Loftus & Mackworth, 1978; Torralba, Oliva, Castelhano, & Henderson, 2006), possibly object recognition within scenes (Boyce & Pollatsek, 1992; Davenport & Potter, 2004; De Graef,”
• Contextual Priming and Feedback for Faster R-CNN (2016, background): “There is ample evidence of the importance of similar top-down contextual priming in the human visual system [15, 39], and its utility in reducing areas to focus our attention on for recognizing objects [13, 14].”
• Contextual expectations in the real-world modulate low-frequency neural oscillations (2025, unknown): “…environments are typically recognised faster and more accurately than objects which appear in unexpected (or incongruent) environments (Bar, 2004; Biederman et al., 1982; Brandman & Peelen, 2017; Cornelissen & Võ, 2017; Davenport & Potter, 2004; Henderson et al., 1999; Loftus & Mackworth, 1978).”