Are All Pixels Equally Important? Towards Multi-Level Salient Object Detection
Related publications (66)
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Viewers of 360-degree videos are provided with both visual modality to characterize their surrounding views and audio modality to indicate the sound direction. Though both modalities are important for saliency prediction, little work has been done by joint ...
Semantic segmentation algorithms that can robustly segment objects across multiple camera viewpoints are crucial for assuring navigation and safety in emerging applications such as autonomous driving. Existing algorithms treat each image in isolation, but ...
Modelling human visual attention is of great importance in the field of computer vision and has been widely explored for 3D imaging. Yet, in the absence of ground truth data, it is unclear whether such predictions are in alignment with the actual human vie ...
Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial systems. A main challenge is the problem of variability: objects can appear across huge ...
The Customer Experience Management at the Swiss Federal Railways (SBB) experiments with new technologies and methods to capture experiences and perceptions of passengers to design safe and customer friendly environments. First, a new methodological approac ...
Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...
The cameras are invented by imitating the human visual system to capture the scene. The camera
technologies have been substantially advanced in recent years. 108 MP resolution with 100x hybrid
zoom has become standard features for smartphone flagships. In ...
A large part of computer vision research is devoted to building models
and algorithms aimed at understanding human appearance and behaviour
from images and videos. Ultimately, we want to build automated systems
that are at least as capable as people when i ...
Automatic prediction of salient regions in images is a well developed topic in the field of computer vision. Yet, virtual reality omnidirectional visual content brings new challenges to this topic, due to a different representation of visual information an ...
Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial systems. A main challenge is the problem of variability: objects can appear across huge ...