Objective. Artificial vision has been and still is the subject of intense research. The ultimate goal is to help blind people in their daily life. Approaches to artificial vision, including visual prostheses and optogenetics, have strongly focused on resto ...
Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...
Eusocial life is characterized by division of labour, collective decision making and self organization, and regarded as the highest form of social organisation in groups. Ants are a model organism for research in collective behavior and the evolution of eu ...
Object detection plays a critical role in various computer vision applications, encompassing
domains like autonomous vehicles, object tracking, and scene understanding. These applica-
tions rely on detectors that generate bounding boxes around known object ...
Objective. The optic nerve is a good location for a visual neuroprosthesis. It can be targeted when a subject cannot receive a retinal prosthesis and it is less invasive than a cortical implant. The effectiveness of an electrical neuroprosthesis depends on ...
We present an approach to bridge the gap between the computational models of human vision and the clinical practice on visual impairments (VI). In a nutshell, we propose to connect advances in neuroscience and machine learning to study the impact of VI on ...
Out-of-body experiences (OBEs) are characterized by the subjective feeling of being located outside one's physical body and perceiving one's own body from an elevated perspective looking downwards. OBEs have been correlated with abnormal integration of bod ...
3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since-without additional prior assumpti ...
We apply inverse reinforcement learning (IRL) with a novel cost feature to the problem of robot navigation in human crowds. Consistent with prior empirical work on pedestrian behavior, the feature anticipates collisions between agents. We efficiently learn ...
Systematic compositionality, or the ability to adapt to novel situations by creating a mental model of the world using reusable pieces of knowledge, remains a significant challenge in machine learning. While there has been considerable progress in the lang ...
How does the visual system represent continuity in the constantly changing visual input? A recent proposal is that vision is serially dependent: Stimuli seen a moment ago influence what we perceive in the present. In line with this, recent frameworks sugge ...
