Related papers: Event-based Star Tracking under Spacecraft Jitter:…
Event cameras are a novel type of sensor designed for capturing the dynamic changes of a scene. Due to factors such as trigger and transmission delays, a time offset exists in the data collected by multiple event cameras, leading to…
In this paper, we present DSERT-RoLL, a driving dataset that incorporates stereo event, RGB, and thermal cameras together with 4D radar and dual LiDAR, collected across diverse weather and illumination conditions. The dataset provides…
Nowadays, more and more datasets are published towards research and development of systems and models, enabling direct comparisons, continuous improvement of solutions, and researchers engagement with experimental, real life data. However,…
Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or exposure artifacts due to their sampling principle. By…
Researchers in natural science need reliable methods for quantifying animal behavior. Recently, numerous computer vision methods emerged to automate the process. However, observing wild species at remote locations remains a challenging task…
A camera begins to sense light the moment we press the shutter button. During the exposure interval, relative motion between the scene and the camera causes motion blur, a common undesirable visual artifact. This paper presents E-CIR, which…
Enabled by large annotated datasets, tracking and segmentation of objects in videos has made remarkable progress in recent years. Despite these advancements, algorithms still struggle under degraded conditions and during fast movements.…
PLAnetary Transits and Oscillations of stars (PLATO) is a medium-class mission belonging to the European Space Agency (ESA) Cosmic Vision programme. The mission payload is composed of 26 telescopes and cameras which will observe…
The neuromorphic event cameras, which capture the optical changes of a scene, have drawn increasing attention due to their high speed and low power consumption. However, the event data are noisy, sparse, and nonuniform in the…
Event cameras offer significant advantages for low-light video enhancement, primarily due to their high dynamic range. Current research, however, is severely limited by the absence of large-scale, real-world, and spatio-temporally aligned…
People often recognize what triggered their stress only after the moment has passed. In therapy, this can become a recurring problem: clients are asked to remember what happened between sessions, but the details that matter (where they…
We then introduce a novel hierarchical knowledge distillation strategy that incorporates the similarity matrix, feature representation, and response map-based distillation to guide the learning of the student Transformer network. We also…
Event cameras triggered a paradigm shift in the computer vision community delineated by their asynchronous nature, low latency, and high dynamic range. Calibration of event cameras is always essential to account for the sensor intrinsic…
Event cameras encode visual information with high temporal precision, low data-rate, and high-dynamic range. Thanks to these characteristics, event cameras are particularly suited for scenarios with high motion, challenging lighting…
Eye-tracking is a vital technology for human-computer interaction, especially in wearable devices such as AR, VR, and XR. The realization of high-speed and high-precision eye-tracking using frame-based image sensors is constrained by their…
When legged robots perform agile movements, traditional RGB cameras often produce blurred images, posing a challenge for rapid perception. Event cameras have emerged as a promising solution for capturing rapid perception and coping with…
Tracking any point (TAP) recently shifted the motion estimation paradigm from focusing on individual salient points with local templates to tracking arbitrary points with global image contexts. However, while research has mostly focused on…
The bio-inspired event camera has garnered extensive research attention in recent years, owing to its significant potential derived from its high dynamic range and low latency characteristics. Similar to the standard camera, the event…
Event-based cameras are biologically inspired sensors that output events, i.e., asynchronous pixel-wise brightness changes in the scene. Their high dynamic range and temporal resolution of a microsecond makes them more reliable than…
Data stream poses additional challenges to statistical classification tasks because distributions of the training and target samples may differ as time passes. Such distribution change in streaming data is called concept drift. Numerous…