DepthFormer: Multimodal Positional Encodings and Cross-Input Attention for Transformer-Based Segmentation Networks

Most approaches for semantic segmentation use only information from color cameras to parse the scenes, yet recent advancements show that using depth data allows to further improve performances. In this work, we focus on transformer-based deep learning architectures, that have achieved state-of-the-art performances on the segmentation task, and we propose to employ depth information by embedding it in the positional encoding. Effectively, we extend the network to multimodal data without adding any parameters and in a natural way that makes use of the strength of transformers' self-attention modules. We also investigate the idea of performing cross-modality operations inside the attention module, swapping the key inputs between the depth and color branches. Our approach consistently improves performances on the Cityscapes benchmark

SynDrone -- Multi-modal UAV Dataset for Urban Scenarios

The development of computer vision algorithms for Unmanned Aerial Vehicles (UAVs) imagery heavily relies on the availability of annotated high-resolution aerial data. However, the scarcity of large-scale real datasets with pixel-level annotations poses a significant challenge to researchers as the limited number of images in existing datasets hinders the effectiveness of deep learning models that require a large amount of training data. In this paper, we propose a multimodal synthetic dataset containing both images and 3D data taken at multiple flying heights to address these limitations. In addition to object-level annotations, the provided data also include pixel-level labeling in 28 classes, enabling exploration of the potential advantages in tasks like semantic segmentation. In total, our dataset contains 72k labeled samples that allow for effective training of deep architectures showing promising results in synthetic-to-real adaptation. The dataset will be made publicly available to support the development of novel computer vision methods targeting UAV applications.Comment: Accepted at ICCV Workshops, downloadable dataset with CC-BY license, 8 pages, 4 figures, 8 table

RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic Segmentation

Catastrophic forgetting of previous knowledge is a critical issue in continual learning typically handled through various regularization strategies. However, existing methods struggle especially when several incremental steps are performed. In this paper, we extend our previous approach (RECALL) and tackle forgetting by exploiting unsupervised web-crawled data to retrieve examples of old classes from online databases. Differently from the original approach that did not perform any evaluation of the web data, here we introduce two novel approaches based on adversarial learning and adaptive thresholding to select from web data only samples strongly resembling the statistics of the no longer available training ones. Furthermore, we improved the pseudo-labeling scheme to achieve a more accurate labeling of web data that also consider classes being learned in the current step. Experimental results show that this enhanced approach achieves remarkable results, especially when multiple incremental learning steps are performed

HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Pose Dataset with Household Objects in Realistic Scenarios

Estimating the 6D pose of objects is a major 3D computer vision problem. Since the promising outcomes from instance-level approaches, research heads also move towards category-level pose estimation for more practical application scenarios. However, unlike well-established instance-level pose datasets, available category-level datasets lack annotation quality and provided pose quantity. We propose the new category-level 6D pose dataset HouseCat6D featuring 1) Multi-modality of Polarimetric RGB and Depth (RGBD+P), 2) Highly diverse 194 objects of 10 household object categories including 2 photometrically challenging categories, 3) High-quality pose annotation with an error range of only 1.35 mm to 1.74 mm, 4) 41 large-scale scenes with extensive viewpoint coverage and occlusions, 5) Checkerboard-free environment throughout the entire scene, and 6) Additionally annotated dense 6D parallel-jaw grasps. Furthermore, we also provide benchmark results of state-of-the-art category-level pose estimation networks

High habitat richness reduces the risk of tick-borne encephalitis in Europe: a multi-scale study

Background The natural transmission cycle of tick-borne encephalitis (TBE) virus is enhanced by complex interactions between ticks and key hosts strongly connected to habitat characteristics. The diversity of wildlife host species and their relative abundance is known to affect transmission of tick-borne diseases. Therefore, in the current context of global biodiversity loss, we explored the relationship between habitat richness and the pattern of human TBE cases in Europe to assess biodiversity's role in disease risk mitigation. Methods We assessed human TBE case distribution across 879 European regions using official epidemiological data reported to The European Surveillance System (TESSy) between 2017 and 2021 from 15 countries. We explored the relationship between TBE presence and the habitat richness index (HRI1) by means of binomial regression. We validated our findings at local scale using data collected between 2017 and 2021 in 227 municipalities located in Trento and Belluno provinces, two known TBE foci in northern Italy. Findings Our results showed a significant parabolic effect of HRI on the probability of presence of human TBE cases in the European regions included in our dataset, and a significant, negative effect of HRI on the local presence of TBE in northern Italy. At both spatial scales, TBE risk decreases in areas with higher values of HRI. Interpretation To our knowledge, no efforts have yet been made to explore the relationship between biodiversity and TBE risk, probably due to the scarcity of high-resolution, large-scale data about the abundance or density of critical host species. Hence, in this study we considered habitat richness as proxy for vertebrate host diversity. The results suggest that in highly diverse habitats TBE risk decreases. Hence, biodiversity loss could enhance TBE risk for both humans and wildlife. This association is relevant to support the hypothesis that the maintenance of highly diverse ecosystems mitigates disease ris

Epidemiology of West Nile virus in Africa: an underestimated threat

12openInternationalInternational coauthor/editorBackground West Nile virus is a mosquito-borne flavivirus which has been posing continuous challenges to public health worldwide due to the identification of new lineages and clades and its ability to invade and establish in an increasing number of countries. Its current distribution, genetic variability, ecology, and epidemiological pattern in the African continent are only partially known despite the general consensus on the urgency to obtain such information for quantifying the actual disease burden in Africa other than to predict future threats at global scale. Methodology and principal findings References were searched in PubMed and Google Scholar electronic databases on January 21, 2020, using selected keywords, without language and date restriction. Additional manual searches of reference list were carried out. Further references have been later added accordingly to experts’ opinion. We included 153 scientific papers published between 1940 and 2021. This review highlights: (i) the co-circulation of WNV-lineages 1, 2, and 8 in the African continent; (ii) the presence of diverse WNV competent vectors in Africa, mainly belonging to the Culex genus; (iii) the lack of vector competence studies for several other mosquito species found naturally infected with WNV in Africa; (iv) the need of more competence studies to be addressed on ticks; (iv) evidence of circulation of WNV among humans, animals and vectors in at least 28 Countries; (v) the lack of knowledge on the epidemiological situation of WNV for 19 Countries and (vii) the importance of carrying out specific serological surveys in order to avoid possible bias on WNV circulation in Africa. Conclusions This study provides the state of art on WNV investigation carried out in Africa, highlighting several knowledge gaps regarding i) the current WNV distribution and genetic diversity, ii) its ecology and transmission chains including the role of different arthropods and vertebrate species as competent reservoirs, and iii) the real disease burden for humans and animals. This review highlights the needs for further research and coordinated surveillance efforts on WNV in Africa.openMencattelli, G.; Dior Ndione M.H.; Rosa', R.; Marini, G.; Diagne, C.T.; Diagne, M.M.; Fall, G.; Faye, O.; Diallo, M.; Faye, O.; Savini, G.; Rizzoli, A.Mencattelli, G.; Dior Ndione, M.H.; Rosa', R.; Marini, G.; Diagne, C.T.; Diagne, M.M.; Fall, G.; Faye, O.; Diallo, M.; Faye, O.; Savini, G.; Rizzoli, A

West Nile Virus lineage 1 in Italy: newly introduced or a re-occurrence of a previously circulating strain?

In Italy, West Nile virus (WNV) appeared for the first time in the Tuscany region in 1998. After 10 years of absence, it re-appeared in the areas surrounding the Po River delta, affecting eight provinces in three regions. Thereafter, WNV epidemics caused by genetically divergent isolates have been documented every year in the country. Since 2018, only WNV Lineage 2 has been reported in the Italian territory. In October 2020, WNV Lineage 1 (WNV-L1) re-emerged in Italy, in the Campania region. This is the first occurrence of WNV-L1 detection in the Italian territory since 2017. WNV was detected in the internal organs of a goshawk (Accipiter gentilis) and a kestrel (Falco tinnunculus). The RNA extracted in the goshawk tissue samples was sequenced, and a Bayesian phylogenetic analysis was performed by a maximum-likelihood tree. Genome analysis, conducted on the goshawk WNV complete genome sequence, indicates that the strain belongs to the WNV-L1 Western-Mediterranean (WMed) cluster. Moreover, a close phylogenetic similarity is observed between the goshawk strain, the 2008–2011 group of Italian sequences, and European strains belonging to the Wmed cluster. Our results evidence the possibility of both a new re-introduction or unnoticed silent circulation in Italy, and the strong importance of keeping the WNV surveillance system in the Italian territory activ

West Nile Virus lineage 2 overwintering in Italy

In January 2022, West Nile virus (WNV) lineage 2 (L2) was detected in an adult female goshawk rescued near Perugia in the region of Umbria (Italy). The animal showed neurological symptoms and died 15 days after its recovery in a wildlife rescue center. This was the second case of WNV infection recorded in birds in the Umbria region during the cold season, when mosquitoes, the main WNV vectors, are usually not active. According to the National Surveillance Plan, the Umbria region is included amongst the WNV low-risk areas. The necropsy evidenced generalized pallor of the mucous membranes, mild splenomegaly, and cerebral edema. WNV L2 was detected in the brain, heart, kidney, and spleen homogenate using specific RT-PCR. Subsequently, the extracted viral RNA was sequenced. A Bayesian phylogenetic analysis performed through a maximum-likelihood tree showed that the genome sequence clustered with the Italian strains within the European WNV strains among the central-southern European WNV L2 clade. These results, on the one hand, confirmed that the WNV L2 strains circulating in Italy are genetically stable and, on the other hand, evidenced a continuous WNV circulation in Italy throughout the year. In this report case, a bird-to-bird WNV transmission was suggested to support the virus overwintering. The potential transmission through the oral route in a predatory bird may explain the relatively rapid spread of WNV, as well as other flaviviruses characterized by similar transmission patterns. However, rodent-to-bird transmission or mosquito-to-bird transmission cannot be excluded, and further research is needed to better understand WNV transmission routes during the winter season in Ital

Efficacy and safety of intravesical fibrin glue instillation for management of patients with refractory hemorrhagic cystitis: 12-months results. A promising therapy for hemorrhagic cystitis.

Objectives: Fibrin glue (FG) endo-vesical application seems to be a promising therapy for hemorrhagic cystitis (HC). We aimed to evaluate efficacy and safety of FG instillation in patients with HC. Methods: Patients with HC not responsive to conventional treatments (bladder irrigation, catheterization, blood transfusions, hyperhydration and endoscopic coagulation) were treated with FG endo-vesical instillation (April 2017- December 2018). FG was prepared from 120 mL of patient blood with the Vivostat® system. After standard cystoscopy, bladder was insufflated with carbon dioxide (CO2) according to bladder compliance and autologous FG was applied to bladder wall and bleeding sites. Results: Ten patients included with grade 2 or higher HC secondary to bone marrow graft for hematological diseases (30%) or to actinic cystitis caused by prostate cancer radiotherapy (RT) (70%). The median HC onset time after RT was 4.8 (IQR 3.9- 6.3) years and 35 (IQR 27.5-62.5) days after hematopoietic stem cell transplantation (HSCT). Five patients had a complete response after one treatment, three patients had clinical response (grade < 2 hematuria, amelioration of symptoms), one of them required catheterization and bladder irrigation. One patient required a second instillation of FG achieving a clinical response. No adverse events related to the procedure were recorded, however one patient died for causes not related to the procedure. Median Interstitial Cystitis Symptoms Index was 13.0 (IQR 11.0-15.0) pre-operatively and 4.0 (IQR 2.0-5.0) post-operatively. Conclusions: Our study showed that, even in hematological patients, autologous FG instillation maybe a safe, repeatable and effective treatment modality in patients with refractory HC