Related papers: TRANSLIENT: Detecting Transients Resulting from Po…
Machine learning on data streams is increasingly more present in multiple domains. However, there is often data distribution shift that can lead machine learning models to make incorrect decisions. While there are automatic methods to…
Background subtraction has been a driving engine for many computer vision and video analytics tasks. Although its many variants exist, they all share the underlying assumption that photometric scene properties are either static or exhibit…
This paper addresses the problem of detecting relevant motion caused by objects of interest (e.g., person and vehicles) in large scale home surveillance videos. The traditional method usually consists of two separate steps, i.e., detecting…
Detecting moving objects in dynamic scenes from sequences of lidar scans is an important task in object tracking, mapping, localization, and navigation. Many works focus on changes detection in previously observed scenes, while a very…
Temporal sampling does more than add another axis to the vector of observables. Instead, under the recognition that how objects change (and move) in time speaks directly to the physics underlying astronomical phenomena, next-generation…
The near future of astrophysics involves many large solid-angle, multi-epoch, multi-band imaging surveys. These surveys will, at their faint limits, have data on large numbers of sources that are too faint to be detected at any individual…
The unique capabilities of Swift that make it ideal for discovery and follow-up of Gamma-Ray bursts also makes it the idea mission for discovery and monitoring of X-ray Transients in the Milky Way and the Large and Small Magellanic Clouds.…
X-ray transients are among the most enigmatic objects in the cosmic sky. The unpredictability and underlying nature of their transient behavior has prompted much study in recent years. While significant progress has been made in this field,…
We introduce a novel motion estimation method, MaskFlow, that is capable of estimating accurate motion fields, even in very challenging cases with small objects, large displacements and drastic appearance changes. In addition to lower-level…
Camera fingerprint detection plays a crucial role in source identification and image forensics, with wavelet denoising approaches proving to be particularly effective in extracting sensor pattern noise (SPN). In this article, we propose a…
Recurrent Neural Network, Long Short-Term Memory, and Transformer have made great progress in predicting the trajectories of moving objects. Although the trajectory element with the surrounding scene features has been merged to improve…
Future surveys such as the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will observe an order of magnitude more astrophysical transient events than any previous survey before. With this deluge of photometric data,…
3D object detection is essential in autonomous driving, providing vital information about moving objects and obstacles. Detecting objects in distant regions with only a few LiDAR points is still a challenge, and numerous strategies have…
[abridged] In large-scale time-domain surveys, the processing of data, from procurement up to the detection of sources, is generally automated. One of the main challenges is contamination by artifacts, especially in regions of strong…
The detrending algorithms which are widely used to reduce the impact of stellar variability on space-based transit surveys are ill-suited for estimating the parameters of confirmed planets, as they unavoidably alter the transit signal. We…
The development of the observing strategy for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) requires a broad optimization across science cases inside and outside of time-domain astronomy. We introduce a novel metric…
The \hi 21 cm transition line is expected to be an important probe into the cosmic dark ages and epoch of reionization. Foreground source removal is one of the principal challenges for the detection of this signal. This paper investigates…
Salient object detection or salient region detection models, diverging from fixation prediction models, have traditionally been dealing with locating and segmenting the most salient object or region in a scene. While the notion of most…
Transit photometry is perhaps the most successful method for detecting exoplanets to date. However, a substantial amount of signal processing is needed since the dip in the signal detected, an indication that there is a planet in transit,…
The progenitors for many types of supernovae (SNe) are still unknown, and an approach to diagnose their physical origins is to investigate the light curve brightness and shape of a large set of SNe. However, it is often difficult to compare…