In this work we seek to move away from the traditional paradigm for 2D object recognition whereby objects are identified in the image as 2D bounding boxes. We focus instead on: i...
Current computational models of visual attention focus on bottom-up information and ignore scene context. However, studies in visual cognition show that humans use context to faci...
Aude Oliva, Antonio B. Torralba, Monica S. Castelh...
— A biologically inspired foveated attention system in an object detection scenario is proposed. Thereby, a highperformance active multi-focal camera system imitates visual behav...
In this work we deal with the problem of modelling and exploiting the interaction between the processes of image segmentation and object categorization. We propose a novel framewo...
In order for recognition systems to scale to a larger number of object categories building visual class taxonomies is important to achieve running times logarithmic in the number o...