Enhanced Boundary Learning for Glass-like Object Segmentation

Glass-like objects such as windows, bottles, and mirrors exist widely in the real world. Sensing these objects has many applications, including robot navigation and grasping. However, this task is very challenging due to the arbitrary scenes behind glass-like objects. This paper aims to solve the glass-like object segmentation problem via enhanced boundary learning. In particular, we first propose a novel refined differential module that outputs finer boundary cues. We then introduce an edge-aware point-based graph convolution network module to model the global shape along the boundary. We use these two modules to design a decoder that generates accurate and clean segmentation results, especially on the object contours. Both modules are lightweight and effective: they can be embedded into various segmentation models. In extensive experiments on three recent glass-like object segmentation datasets, including Trans10k, MSD, and GDD, our approach establishes new state-of-the-art results. We also illustrate the strong generalization properties of our method on three generic segmentation datasets, including Cityscapes, BDD, and COCO Stuff. Code and models is available at \url{https://github.com/hehao13/EBLNet}.Comment: ICCV-2021 Code is availabe at https://github.com/hehao13/EBLNe

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

Aerial Image Segmentation is a particular semantic segmentation problem and has several challenging characteristics that general semantic segmentation does not have. There are two critical issues: The one is an extremely foreground-background imbalanced distribution, and the other is multiple small objects along with the complex background. Such problems make the recent dense affinity context modeling perform poorly even compared with baselines due to over-introduced background context. To handle these problems, we propose a point-wise affinity propagation module based on the Feature Pyramid Network (FPN) framework, named PointFlow. Rather than dense affinity learning, a sparse affinity map is generated upon selected points between the adjacent features, which reduces the noise introduced by the background while keeping efficiency. In particular, we design a dual point matcher to select points from the salient area and object boundaries, respectively. Experimental results on three different aerial segmentation datasets suggest that the proposed method is more effective and efficient than state-of-the-art general semantic segmentation methods. Especially, our methods achieve the best speed and accuracy trade-off on three aerial benchmarks. Further experiments on three general semantic segmentation datasets prove the generality of our method. Code will be provided in (https: //github.com/lxtGH/PFSegNets).Comment: accepted by CVPR202

Genome-wide characterization of the biggest grass, bamboo, based on 10,608 putative full-length cDNA sequences

<p>Abstract</p> <p>Background</p> <p>With the availability of rice and sorghum genome sequences and ongoing efforts to sequence genomes of other cereal and energy crops, the grass family (Poaceae) has become a model system for comparative genomics and for better understanding gene and genome evolution that underlies phenotypic and ecological divergence of plants. While the genomic resources have accumulated rapidly for almost all major lineages of grasses, bamboo remains the only large subfamily of Poaceae with little genomic information available in databases, which seriously hampers our ability to take a full advantage of the wealth of grass genomic data for effective comparative studies.</p> <p>Results</p> <p>Here we report the cloning and sequencing of 10,608 putative full length cDNAs (FL-cDNAs) primarily from Moso bamboo, <it>Phyllostachys heterocycla </it>cv. <it>pubescens</it>, a large woody bamboo with the highest ecological and economic values of all bamboos. This represents the third largest FL-cDNA collection to date of all plant species, and provides the first insight into the gene and genome structures of bamboos. We developed a Moso bamboo genomic resource database that so far contained the sequences of 10,608 putative FL-cDNAs and nearly 38,000 expressed sequence tags (ESTs) generated in this study.</p> <p>Conclusion</p> <p>Analysis of FL-cDNA sequences show that bamboo diverged from its close relatives such as rice, wheat, and barley through an adaptive radiation. A comparative analysis of the lignin biosynthesis pathway between bamboo and rice suggested that genes encoding caffeoyl-CoA O-methyltransferase may serve as targets for genetic manipulation of lignin content to reduce pollutants generated from bamboo pulping.</p

Tie them up tight: wrapping by Philoponella vicinaspiders breaks, compresses and sometimes kills their prey

We show that uloborid spiders, which lack the poison glands typical of nearly all other spiders, employ thousands of wrapping movements with their hind legs and up to hundreds of meters of silk line to make a shroud that applies substantial compressive force to their prey. Shrouds sometimes break the prey’s legs, buckle its compound eyes inward, or kill it outright. The compressive force apparently results from the summation of small tensions on sticky lines as they are applied to the prey package. Behavioral details indicate that wrapping is designed to compact prey; in turn, compaction probably functions to facilitate these spiders’ unusual method of feeding. This is the first demonstration that prey wrapping by spiders compacts and physically damages their prey, rather than simply restraining them.Instituto Smithsoniano de Investigaciones Tropicales (STRI)Universidad de Costa RicaUCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Biologí

The evolution of prey‐wrapping behaviour in spiders

We traced the evolution of silk use by spiders in attacks on prey by combining previous publications with new observations of 31 species in 16 families. Two new prey‐wrapping techniques are described. One, in which the spider holds a tense line (often covered with viscid silk) with both legs IV and applies it to the prey with a simultaneous movement of both legs, may be a synapomorphy linking Theridiidae, Nesticidae, and Synotaxidae. The other, in which the spider stands over the prey and turns in place, is apparently very ancient; it occurs in Theraphosidae, Tengellidae, and Agelenidae. The use of legs IV to wrap prey is described for the first time in Filistatidae and Scytodidae. Using a recent phylogeny of spiders, we propose that prey wrapping with legs IV has evolved convergently at least four times. We propose that prey wrapping originally evolved from egg‐sac construction behaviour.Instituto Smithsoniano de Investigaciones Tropicales (STRI)Universidad de Costa RicaUCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Biologí

Space advanced technology demonstration satellite

The Space Advanced Technology demonstration satellite (SATech-01), a mission for low-cost space science and new technology experiments, organized by Chinese Academy of Sciences (CAS), was successfully launched into a Sun-synchronous orbit at an altitude of similar to 500 km on July 27, 2022, from the Jiuquan Satellite Launch Centre. Serving as an experimental platform for space science exploration and the demonstration of advanced common technologies in orbit, SATech-01 is equipped with 16 experimental payloads, including the solar upper transition region imager (SUTRI), the lobster eye imager for astronomy (LEIA), the high energy burst searcher (HEBS), and a High Precision Magnetic Field Measurement System based on a CPT Magnetometer (CPT). It also incorporates an imager with freeform optics, an integrated thermal imaging sensor, and a multi-functional integrated imager, etc. This paper provides an overview of SATech-01, including a technical description of the satellite and its scientific payloads, along with their on-orbit performance

Assembly of Silver Nanoparticles in Pearl-Necklace-Like Nanostructure Using a Polyelectrolyte

Program for New Century Excellent Talents in Fujian Province [X12103]; Scientific Research Foundation for the Returned Overseas Chinese Scholars, the Ministry of Education [K13003]; Natural Science Foundation of China [20701031]; Natural Science FoundatioPearl-necklace-like Ag nanostructures are prepared with microwave irradiation in a one-step process using polymethacrylic acid (PMAA) as a reducing agent, and AgNO(3) as a silver precursor without other chemical agent in a 6.5 <= pH <= 8.0 aqueous solution. Derjaguin-Landau-Verwey-Overbeek theory is used to calculate the stability of Ag particles in the aqueous medium. The calculated results are fairly consistent with the experimental results. The formation mechanism of pearl-necklace-like silver nanostructures is suggested as three steps: immobilization of Ag(+) ions with the PMAA template, reduction of Ag(+) ions with PMAA under microwave irradiation, anisotropic self-assembly of silver particles capped by the negatively charged PMAA with electrostatic interactions and Van der Waals forces

Boundarysqueeze: Image segmentation as boundary squeezing

This paper proposes a novel method for high-quality image segmentation of both objects and scenes. Inspired by the dilation and erosion operations in morphological image processing techniques, the pixel-level image segmentation problems are treated as squeezing object boundaries. From this perspective, a novel and efficient \textbf{Boundary Squeeze} module is proposed. This module is used to squeeze the object boundary from both inner and outer directions, which contributes to precise mask representation. A bi-directionally flow-based warping process is proposed to generate such squeezed feature representation, and two specific loss signals are designed to supervise the squeezing process. The Boundary Squeeze module can be easily applied to both instance and semantic segmentation tasks as a plug-and-play module by building on top of some existing methods. Moreover, the proposed module is light-weighted, and thus has potential for practical usage. Experiment results show that our simple yet effective design can produce high-quality results on several different datasets. Besides, several other metrics on the boundary are used to prove the effectiveness of our method over previous work. Our approach yields significant improvement on challenging COCO and Cityscapes datasets for both instance and semantic segmentation, and outperforms previous state-of-the-art PointRend in both accuracy and speed under the same setting. Codes and models will be published at \url{https://github.com/lxtGH/BSSeg}