FoV
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Predicting Dynamic Map States from Limited Field-of-View Sensor Data
arXiv:2602.12360v2 Announce Type: replace Abstract: When autonomous systems are deployed in real-world scenarios, sensors are often subject to limited field-of-view (FOV) constraints, either naturally through system design, or through unexpected occlusions or sensor failures. In conditions where a large FOV is unavailable, it is important to be able to infer information about the environment and predict the state of nearby surroundings based on available data to maintain safe and accurate...
Pantheon360: Taming Digital Twin Generation via 3D-Aware 360{\deg} Video Diffusion
Announce Type: replace Abstract: Generating complete digital twins from videos requires precise camera control, global scene coverage, and strict spatial-temporal consistency constraints that remain challenging for perspective video generators due to their limited field of view (FoV). Their narrow FoV forces long or multi-view trajectories, amplifying cross-view inconsistency and temporal drift.
Wide-field mid-infrared single-photon upconversion imaging
arXiv:2606.03206v1 Announce Type: new Abstract: Frequency upconversion technique, where the infrared signal is nonlinearly translated into the visible band to leverage the silicon sensors, offers a promising alternation for the mid-infrared (MIR) imaging. However, the intrinsic field of view (FOV) is typically limited by the phase-matching condition, thus imposing a remaining challenge to promote subsequent applications. Here, we demonstrate a wide-field upconversion imaging based on the...
PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion
arXiv:2606.03441v1 Announce Type: new Abstract: Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to the limited field of view (FOV). In this paper, we propose PerchRL, a reinforcement learning (RL) framework for vision-based agile perching on inclined platforms under rapid and irregular motion. Specifically, we employ a two-stage learning strategy consisting of state-based pre-training followed by...
Distortion-Aware PETR for BEV Object Detection with Mixed Pinhole-Fisheye Cameras
arXiv:2606.08680v1 Announce Type: new Abstract: Fisheye cameras are widely deployed in autonomous driving perception suites for their low cost and full-coverage field of view (FOV), yet their potential remains underleveraged in 3D object detection. Severe radial distortion challenges most BEV detectors by violating the fundamental assumption of uniform sampling.
Texture-preserving implicit neural representation for Cone beam CT truncated reconstruction
arXiv:2606.06039v1 Announce Type: new Abstract: Cone-beam computed tomography (CBCT) frequently suffers from data truncation, which introduces severe artifacts and limits the effective field of view (FOV). Existing deep learning methods for truncated cone-beam computed tomography (CBCT) reconstruction suffer from serious limitations, including a strict reliance on supervised ground truth and a failure to account for continuous 3D spatial truncation variations. To address these challenges, we...
PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion
arXiv:2606.03441v2 Announce Type: replace Abstract: Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to the limited field of view (FOV). In this paper, we propose PerchRL, a reinforcement learning (RL) framework for vision-based agile perching on inclined platforms under rapid and irregular motion. Specifically, we employ a two-stage learning strategy consisting of state-based pre-training...
Constraining reionization morphology and source properties with 21cm galaxy cross-correlation surveys
arXiv:2601.18627v2 Announce Type: replace-cross Abstract: Cross-correlations between 21cm observations and galaxy surveys provide a powerful probe of reionization by providing robustness against foreground contamination while linking ionization morphology to galaxies. We quantified the constraining power of 21cm galaxy cross-power spectra for inferring the neutral hydrogen fraction, $x_\mathrm{HI}(z),$ and mean overdensity, $\langle 1+\delta_\mathrm{HI} \rangle(z)$, exploring dependence on...
Foveated-Imaging Geometry CT Architecture and Seeded Diffusion Model Enabling Global Super-Resolution Reconstruction
Announce Type: new Abstract: For X-ray computed tomography (CT), a smaller detector pixel size generally leads to higher scanner spatial resolution, but inevitably increases system cost as well as data overhead in acquisition and processing. To achieve high-resolution (HR) CT imaging in a more resource-efficient manner, we propose a Foveated-Imaging Geometry CT (FIGCT) architecture, which integrates local HR data into an acquisition scheme dominated by low-resolution (LR) measurements. We...
UniSHARP: Universal Sharp Monocular View Synthesis
Announce Type: new Abstract: In this work, we focus on extending SHARP, the popular photorealistic view synthesis method, for universal monocular rendering across a continuum of camera systems, from conventional perspective cameras to wide-field-of-view, fisheye and omnidirectional panoramic settings. To overcome the pinhole-specific assumptions of SHARP, our key idea is to align various images in a unified omnidirectional latent space. Thus, we propose UniSHARP, which performs implicit...