Learning Single-Image Depth from Videos using Quality Assessment Networks

Depth estimation from a single image in the wild remains a challenging problem. One main obstacle is the lack of high-quality training data for images in the wild. In this paper we propose a method to automatically generate such data through Structure-from-Motion (SfM) on Internet videos. The core of this method is a Quality Assessment Network that identifies high-quality reconstructions obtained from SfM. Using this method, we collect single-view depth training data from a large number of YouTube videos and construct a new dataset called YouTube3D. Experiments show that YouTube3D is useful in training depth estimation networks and advances the state of the art of single-view depth estimation in the wild

Robust Dense Mapping for Large-Scale Dynamic Environments

We present a stereo-based dense mapping algorithm for large-scale dynamic urban environments. In contrast to other existing methods, we simultaneously reconstruct the static background, the moving objects, and the potentially moving but currently stationary objects separately, which is desirable for high-level mobile robotic tasks such as path planning in crowded environments. We use both instance-aware semantic segmentation and sparse scene flow to classify objects as either background, moving, or potentially moving, thereby ensuring that the system is able to model objects with the potential to transition from static to dynamic, such as parked cars. Given camera poses estimated from visual odometry, both the background and the (potentially) moving objects are reconstructed separately by fusing the depth maps computed from the stereo input. In addition to visual odometry, sparse scene flow is also used to estimate the 3D motions of the detected moving objects, in order to reconstruct them accurately. A map pruning technique is further developed to improve reconstruction accuracy and reduce memory consumption, leading to increased scalability. We evaluate our system thoroughly on the well-known KITTI dataset. Our system is capable of running on a PC at approximately 2.5Hz, with the primary bottleneck being the instance-aware semantic segmentation, which is a limitation we hope to address in future work. The source code is available from the project website (http://andreibarsan.github.io/dynslam).Comment: Presented at IEEE International Conference on Robotics and Automation (ICRA), 201

Design and performance of the first IceAct demonstrator at the South Pole

In this paper we describe the first results of IceAct, a compact imaging air-Cherenkov telescope operating in coincidence with the IceCube Neutrino Observatory (IceCube) at the geographic South Pole. An array of IceAct telescopes (referred to as the IceAct project) is under consideration as part of the IceCube-Gen2 extension to IceCube. Surface detectors in general will be a powerful tool in IceCube-Gen2 for distinguishing astrophysical neutrinos from the dominant backgrounds of cosmic-ray induced atmospheric muons and neutrinos: the IceTop array is already in place as part of IceCube, but has a high energy threshold. Although the duty cycle will be lower for the IceAct telescopes than the present IceTop tanks, the IceAct telescopes may prove to be more effective at lowering the detection threshold for air showers. Additionally, small imaging air-Cherenkov telescopes in combination with IceTop, the deep IceCube detector or other future detector systems might improve measurements of the composition of the cosmic ray energy spectrum. In this paper we present measurements of a first 7-pixel imaging air Cherenkov telescope demonstrator, proving the capability of this technology to measure air showers at the South Pole in coincidence with IceTop and the deep IceCube detector

Towards a radiocarbon calibration for oxygen isotope stage 3 using New Zealand kauri (Agathis australis)

It is well known that radiocarbon years do not directly equate to calendar time. As a result, considerable effort has been devoted to generating a decadally resolved calibration curve for the Holocene and latter part of the last termination. A calibration curve that can be unambiguously attributed to changes in atmospheric ¹⁴C content has not, however, been generated beyond 26 kyr cal BP, despite the urgent need to rigorously test climatic, environmental, and archaeological models. Here, we discuss the potential of New Zealand kauri (Agathis australis) to define the structure of the ¹⁴C calibration curve using annually resolved tree rings and thereby provide an absolute measure of atmospheric ¹⁴C. We report bidecadally sampled ¹⁴C measurements obtained from a floating 1050-yr chronology, demonstrating repeatable ¹⁴C measurements near the present limits of the dating method. The results indicate that considerable scope exists for a high-resolution ¹⁴C calibration curve back through OIS-3 using subfossil wood from this source